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AI Engineer 1. Organization Overview (Concise & Neutral) A fast‑growing oncology‑focused organization is reinventing how clinical trials operate by integrating them tightly with real‑world clinical practice. Cross‑disciplinary teams across healthcare, engineering, AI, and regulatory domains work in a Human‑in‑the‑Loop (HITL) model to deliver regulatory‑grade outcomes that expand trial access and accelerate cancer drug development. What’s Different • Clinical trials are embedded within clinical practice—not run in parallel., • Hybrid model blending expert abstraction, AI/NLP/LLMs, and EMR integrations., • Strong commitment to rigorous testing, validation, privacy, and ethical AI., • Mission‑driven culture with high collaboration and urgency. Why Join Now • AI is essential to scaling the business—impact is immediate and visible., • Opportunity to build an end‑to‑end applied AI stack powering clinical teams., • Work across LLMs, CV, and multimodal use cases with strong platform engineering partners. 2. Role Overview — AI Engineer Purpose Design and deliver applied AI systems (LLMs/CV/multimodal) that automate clinical variable extraction and clinical note generation. Work includes repeatable validation, robust documentation, and HITL feedback loops. Strong emphasis on data engineering and backend rigor to ensure model usability and efficiency. Focus Areas • LLM development and LLM‑Ops for text extraction and structuring; some CV/multimodal., • Rapid prototyping with high software‑engineering hygiene., • Statistical validation plans, experiment design, and metrics ownership., • HITL workflow development to reduce manual QA and improve throughput., • Collaboration with Platform Engineering for production alignment., • Comprehensive documentation: datasets, experiments, model cards, QA audits., • Build AI models and pipelines across EMR/EHR, imaging, and clinical documents., • Translate ambiguous clinical requirements into measurable ML objectives., • Define metrics, design experiments, and estimate/model error., • Lead interim QA audit processes and evolve toward AI‑assisted QA., • Partner with data/platform engineers on scalability, data flow, and observability., • Deliver validated AI components for abstraction and note generation., • Meaningfully reduce manual QA workload through HITL optimization., • Standardize testing and documentation frameworks., • Establish efficient PySpark/SQL/Postgres data‑manipulation patterns that accelerate iteration. 3. Product & AI Context In‑Flight Work • LLM‑powered abstraction and clinical note generation with HITL., • Drive productivity gains for internal labeling/abstraction teams., • Data engineering is a major part of the role: PySpark, SQL/Postgres, query optimization, cloud data tooling. 4. Ideal Candidate Profile Background • MSc/PhD in CS, EE, Applied Math, Stats, Physics, or equivalent depth via experience., • 2–5+ years in AI/ML engineering or applied data science., • Expert‑level Python + strong software engineering practices., • Deep learning experience with PyTorch or TensorFlow (LLMs and/or CV)., • Data engineering: PySpark, SQL, Postgres, data modeling, query tuning., • Cloud data platforms (Databricks, S3/Snowflake/Azure/GCP)., • Experiment design, statistical validation, and error analysis., • Additional languages: R, Java, C++., • MLOps fundamentals (versioning, lineage, CI/CD)., • Prior oncology or clinical trials exposure.

About Us ___ is a research lab pioneering human computing. We’re building AI Humans: a new interface that closes the gap between people and machines, free from the friction of today’s systems. Our real-time human simulation models let machines see, hear, respond, and even look real—enabling meaningful, face-to-face conversations. AI Humans combine the emotional intelligence of humans with the reach and reliability of machines, making them capable, trusted agents available 24/7, in every language, on our terms. Imagine a therapist anyone can afford. A personal trainer that adapts to your schedule. A fleet of medical assistants that can give every patient the attention they need. With Tavus, individuals, enterprises, and developers can all build AI Humans to connect, understand, and act with empathy at scale. We’re a Series A company backed by world-class investors including Sequoia Capital, Y Combinator, and Scale Venture Partners. Be part of shaping a future where humans and machines truly understand each other. The Role We’re hiring a Senior AI Researcher to lead research in audio-visual avatar generation. This role is for someone who thrives in ambiguity, has a track record of pushing generative models to new frontiers, and wants to define what human–AI interaction looks like in practice. Your Mission 🚀 • Lead research efforts on audio-visual generation for avatars (Neural Avatars, Talking-Heads), with a focus on conversational settings., • Design models that are coupled with conversation flow — capturing and generating verbal + non-verbal signals in sync., • Drive innovation in diffusion models, long-video generation, and audio-visual modeling., • Translate research into production by partnering with Applied ML and engineering., • Mentor researchers, set research directions, and publish impactful work. You’ll Bring: • A PhD or equivalent research experience, plus 2–3+ years of hands-on experience applying generative models at scale., • Expertise in diffusion models and awareness of the latest efficiency techniques., • Experience in multimodal generation — spanning video, audio, and language., • Proven innovation in long-video generation and/or audio generation., • Excellent programming skills — fluent in PyTorch and GPU-optimized workflows., • Track record of publications in top-tier venues (CVPR, NeurIPS, BMVC, ICASSP, etc.)., • Experience leading research activities or mentoring teams. Nice-to-Haves • Skills in 3D graphics, Gaussian splatting, or large-scale training setups., • Broad exposure to generative AI models beyond your specialty., • Familiarity with software development best practices. Location Preferred: San Francisco (hybrid) or London (office opening soon). Remote within U.S. or Europe considered for exceptional candidates.

Brahma is conducting this search on behalf of our client. We're hiring across quantitative and machine learning roles and looking for strong talent at the intersection of rigorous analysis and applied impact. Whether your background skews toward research, engineering, or analytics, if you think in numbers and build with data, we want to talk. These are not cookie-cutter roles. You'll work on high-ambiguity problems, collaborate across disciplines, and be expected to go from exploratory analysis all the way through to deployed solutions. What You'll Do • Design and build machine learning models, statistical methods, and quantitative frameworks, • Work with large, complex datasets to surface actionable signals, • Run experiments, measure outcomes, and iterate rigorously, • Partner with engineering, product, and business stakeholders to drive decisions, • Communicate findings clearly to technical and non-technical audiences alike What We're Looking For • Advanced degree (MS or PhD) in a quantitative discipline — statistics, mathematics, CS, physics, operations research, or equivalent experience, • Strong foundations in probability, statistics, linear algebra, and optimization, • Proficiency in Python and relevant ML libraries (PyTorch, TensorFlow, scikit-learn, etc.), • Experience with SQL and large-scale data, • Ability to move fluidly between ambiguous research and production-quality work Nice to Have • Domain experience in [NLP / computer vision / time series / causal inference / reinforcement learning], • MLOps and cloud platform experience (AWS, GCP, Azure), • Published research, open-source contributions, or competition track record

🚀 Our client is hiring: Applied Research Engineer (Video AI / Computer Vision) 📍 In-person | San Francisco Our client is building high-performance systems to understand video at internet scale. Video now accounts for ~80% of internet traffic and is rapidly becoming the foundation for creativity, communication, gaming, AR/VR, and robotics. The limiting factor in next-generation AI isn’t models — it’s high-quality video data and understanding at scale. This team sits at the intersection of: • Computer Vision, • Audio + speech processing, • Multimodal AI systems, • Large-scale data infrastructure Their mission is to transform raw video into structured, usable datasets and systems that unlock frontier model performance. 🧠 The role As an Applied Research Engineer, you’ll design and build systems that power large-scale video understanding. You’ll work across both research and production, including: • Building high-performance data and inference pipelines, • Improving model performance through smart preprocessing and optimisation, • Working with APIs, models, and multimodal systems, • Solving ambiguous, research-heavy engineering problems, • Shipping end-to-end systems that directly impact customers and model capability 🔧 What they’re looking for • 2+ years experience in Computer Vision or Audio ML, • Strong Python engineering skills, • Experience with PyTorch or similar ML frameworks, • Ability to work across research + production environments, • Strong communication skills with technical and non-technical stakeholders, • Clean, production-quality coding practices, • Ability to translate customer problems into technical system design, • Passion for video, media, or multimodal AI systems ⭐ Bonus • Open-source contributions, • Early-stage startup experience, • Portfolio of applied ML or systems work 📍 Must be based in or willing to work in-person in San Francisco. If you’re interested in building systems that turn video into intelligence at scale, our client would like to hear from you.

Title: Founding AI Engineer (Research & Systems) Target: PhDs & Research Masters from Stanford, MIT, Berkeley, CMU focused on AI, ML, NLP, Agents. Location: San Francisco, CA | On-Site Compensation: $160K - $250K | 0.8% - 2.0% Equity Visa Sponsorship: Available (H1B, OPT, F1, TN, O1) About Us We are a seed-stage startup, backed by Khosla Ventures and leading AI researchers, building the next generation of reasoning systems for AI agents. Our mission is to move beyond simple RAG and chain-of-thought, creating models that can dynamically plan, execute, and learn in complex environments. Our technical founder is a former Research Lead from Google DeepMind. The Role We are looking for our first AI hire to own the research and implementation of our core agentic models. You will be responsible for turning groundbreaking research papers into robust, scalable systems. This is a rare opportunity to work on cutting-edge problems like long-horizon planning, tool-use optimization, and self-improving agents, with the compute resources to test your ideas at scale. Ideal Profile • Currently pursuing or recently completed a PhD/MSc in Computer Science, AI, or a related field., • Publication record at top conferences (NeurIPS, ICML, ICLR, ACL) is a huge plus., • Deep, hands-on experience with PyTorch, transformer architectures, and reinforcement learning., • Experience with frameworks like LangChain, LangGraph, or AutoGen is preferred, but a strong fundamental understanding of what they abstract is more important., • You read ML papers and immediately think about the implementation details and edge cases., • You are passionate about both theoretical rigor and shipping code that works. Apply if you've done research in: Multi-agent systems, RLHF, reasoning, planning, memory architectures, or program synthesis.

100% remote. Must reside in Bay Area. Must have prior Start Up experience. About the Role We're looking for a Tech Lead Manager (TLM) to own and drive the AI team building the intelligence layer at the heart of our Client's platform. This is a hybrid IC/management role where you'll spend approximately 70% of your time on hands-on technical work and 30% on people management and team leadership. On the technical side, you'll design, build, and ship the models, agents, and ML systems that power Our Client's predictive and prescriptive capabilities—from forecasting workforce demand and flagging burnout risk to orchestrating LLM- driven planning workflows trained on each customer's historical data. You'll write production code, drive architectural decisions across model training, serving, and Tech Lead Manager, AI 1 evaluation, and set the bar for applied ML quality. On the management side, you'll build, mentor, and grow a high-performing team of ML and AI engineers, owning their career development, performance, and day-to-day delivery. The ideal candidate thrives at the intersection of applied ML depth and people leadership—comfortable context-switching between shipping models and coaching engineers. You'll set the technical direction for your team, partner closely with Product, Design, and Data, and ensure your squad delivers AI capabilities that are reliable, measurable, and shipped at a pace that matches our Clients's growth trajectory. What You'll Do Technical Leadership & Execution (~70%) Own the architecture and delivery of AI features end-to-end—from data ingestion and feature engineering to model training, serving, evaluation, and the product surfaces they power. Design and build the systems behind our Client's forecasting, recommendation, and agentic planning capabilities, including LLM-based pipelines, classical ML models, and hybrid approaches trained on per-customer historical data. Drive engineering excellence: lead architecture discussions for model training and inference infrastructure, set standards for offline/online evaluation, experimentation, and responsible AI, and participate in the full ML lifecycle from problem framing through deployment, monitoring, and on-call. Make pragmatic technical decisions that balance model quality, latency, cost, and long-term system health. Leverage modern infrastructure including PostgreSQL, Redis, Kubernetes, vector stores, and streaming technologies to power our Client's real-time AI workflows. Engage in hands-on coding, model development, code reviews, and performance optimizations, setting the standard for applied ML excellence across the team. Tech Lead Manager, AI 2 Champion AI quality—accuracy, calibration, robustness, latency, and the guardrails that make AI outputs trustworthy in an enterprise context. Implement best practices in evaluation, observability, drift detection, and A/B testing to ensure reliability and measurable customer impact. People Management & Team Leadership (~30%) Manage, mentor, and grow a team of ML engineers and applied AI engineers, owning their career growth, performance reviews, and professional development. Conduct regular 1:1s, provide timely and constructive feedback, and create individual development plans for each report. Foster a culture of psychological safety, trust, accountability, and continuous improvement. Own team planning: scope AI work with Product and Design, participate in sprint planning and Agile ceremonies, and remove blockers. Drive hiring for the team—defining roles, conducting interviews, and making hiring decisions to build a world-class AI engineering team. Maintain team health by monitoring workload, preventing burnout, and ensuring sustainable delivery. Cross-Functional Collaboration Partner with Product Managers and Designers to translate product vision into well-defined AI problem statements and technical plans. Communicate progress, model performance, risks, and trade-offs clearly to engineering leadership and non-technical stakeholders. Collaborate across Engineering, Data, and Platform teams to drive alignment on shared data, features, evaluation infrastructure, and serving systems. What We're Looking For B.S. or M.S. in Computer Science, Machine Learning, or a related field, or equivalent experience. Tech Lead Manager, AI 3 7+ years of hands-on software engineering experience with a strong applied ML background—shipping production ML systems, not just prototypes or research. 2+ years of engineering management or tech lead experience, including direct reports, mentorship, and team-level delivery ownership. Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, or equivalent), plus comfort in at least one backend language (Python, Node.js, or Ruby) for productionizing services. Deep understanding of the applied ML lifecycle: problem framing, data pipelines, feature engineering, training, evaluation, deployment, and monitoring. Hands-on experience with LLMs and modern AI tooling—prompt design, retrieval-augmented generation, fine-tuning, agentic workflows, and evaluation of non-deterministic systems. Proven experience designing, building, and operating scalable ML systems in data-heavy environments. Solid grasp of software engineering best practices: testing, code review, CI/CD, design documentation, reproducibility. Experience with RESTful APIs, relational databases (PostgreSQL), vector databases, and cloud-native architecture (Kubernetes, containerization, microservices). A systems-level thinker who balances model quality with pragmatic, business- aware decision-making around cost, latency, and time-to-ship. Excellent communication skills—you can translate complex ML concepts for both engineers and non-technical stakeholders, and set realistic expectations about what AI can and can't do. Demonstrated ability to balance technical execution with people leadership— comfortable context-switching between shipping models and coaching engineers. Early-stage startup experience (Seed to Series C) preferred—comfortable wearing multiple hats and building in fast-moving environments. Tech Lead Manager, AI 4 Nice to Have Experience building agentic systems, tool-using LLM pipelines, or multi-step reasoning workflows in production. Familiarity with time-series forecasting, recommendation systems, or workforce/operations modeling. Background in MLOps tooling (MLflow, Weights & Biases, Ray, Kubeflow) or large-scale data pipeline orchestration (Airflow, Dagster, Prefect). Experience with real-time analytics and streaming infrastructure such as Redis, Kafka, or Apache Pinot. Experience building and scaling AI teams in a high-growth startup environment. Knowledge of evaluation frameworks for LLM-based systems and experience designing offline/online eval harnesses. Why Join Our Client? High Impact: Deploy technology that changes how enterprises plan, manage, and scale their workforce. Deep Technical Ownership: Work directly in code—not just configure systems—and ship meaningful solutions to real customers. Cross-Functional Exposure: Operate at the intersection of Engineering, Product, and Design. Growth & Learning: Build expertise in enterprise-scale systems, data reliability, and AI-driven automation. Benefits: Competitive compensation, meaningful equity, world-class medical/dental/vision coverage, and a flexible remote-first culture with team events, offsites, and happy hours. If you're passionate about building AI systems at scale, love developing people as much as models, and want to be part of a company growing at rocket speed, we'd love to hear from you.

Brahma is conducting this search on behalf of our client. We're hiring across quantitative and machine learning roles and looking for strong talent at the intersection of rigorous analysis and applied impact. Whether your background skews toward research, engineering, or analytics, if you think in numbers and build with data, we want to talk. These are not cookie-cutter roles. You'll work on high-ambiguity problems, collaborate across disciplines, and be expected to go from exploratory analysis all the way through to deployed solutions. What You'll Do • Design and build machine learning models, statistical methods, and quantitative frameworks, • Work with large, complex datasets to surface actionable signals, • Run experiments, measure outcomes, and iterate rigorously, • Partner with engineering, product, and business stakeholders to drive decisions, • Communicate findings clearly to technical and non-technical audiences alike What We're Looking For • Advanced degree (MS or PhD) in a quantitative discipline — statistics, mathematics, CS, physics, operations research, or equivalent experience, • Strong foundations in probability, statistics, linear algebra, and optimization, • Proficiency in Python and relevant ML libraries (PyTorch, TensorFlow, scikit-learn, etc.), • Experience with SQL and large-scale data, • Ability to move fluidly between ambiguous research and production-quality work Nice to Have • Domain experience in [NLP / computer vision / time series / causal inference / reinforcement learning], • MLOps and cloud platform experience (AWS, GCP, Azure), • Published research, open-source contributions, or competition track record

We are seeking a versatile and pragmatic Applied ML Engineer to contribute across a broad range of machine learning and perception tasks. This role requires someone comfortable wearing many hats—from working with computer vision and sensor fusion models to building lightweight inference pipelines, designing experiments, and fine-tuning model behavior in production. You’ll work closely with a cross-functional team spanning hardware, software, and product to deliver real-world AI solutions that are robust, efficient, and reliable under challenging field conditions. This is an ideal position for someone who thrives on variety, rapidly shifting problem domains, and turning rough ideas into deployed systems. Responsibilities: • Design, train, and evaluate models for tasks ranging from object detection and classification to anomaly detection and sensor-based inference., • Optimize model architectures and inference pipelines for performance on embedded/edge hardware under compute and bandwidth constraints., • Contribute to dataset development and labeling strategy, including data augmentation, synthetic data generation, and domain adaptation., • Support prototyping and experimentation across a variety of AI subfields, including computer vision, signal processing, and multi-modal fusion., • Implement real-time pipelines for processing sensor data on-device and in cloud environments., • Develop tools and scripts for benchmarking, data visualization, and debugging ML model performance., • Stay current with the latest research and tools in machine learning and evaluate their applicability to our product roadmap., • Participate in code reviews, team knowledge sharing, and internal technical documentation., • Must be eligible to obtain/maintain a security clearance. Qualifications: • Master’s or PhD in Computer Vision, Machine Learning, Robotics, or related field. Bachelors candidates considered on a case by case basis., • 4+ years of experience building and deploying machine learning models in production environments., • Proficiency in Python and experience with deep learning frameworks such as PyTorch or TensorFlow., • Comfortable working with a range of data types (images, time-series, geospatial, RF, etc.)., • Experience with edge or embedded ML deployments, including model compression and hardware-aware optimization., • Familiarity with common ML practices including cross-validation, hyperparameter tuning, and model monitoring., • Excellent debugging, experimentation, and problem-solving skills., • Strong collaboration and communication skills with both technical and non-technical team members., • Bonus: experience in maritime, aerospace, or other remote sensing domains., • 4 - 10 years of experience in applied machine learning, building and deploying production models. Pay range and compensation package: Salary $190K - $250K, Equity Competitive equity, Visa sponsorship not available. Equal Opportunity Statement: Hybrid work policy, Hybrid in Arlington, VA or San Francisco, CA. Full-time position, Location Arlington, VA, Boston, MA, San Francisco Bay Area, CA, San Diego, CA, Los Angeles. Tech stack: Python, PyTorch, TensorFlow, Computer Vision, Signal Processing, Edge ML, Embedded Systems, World Models.

Job DescriptionMember of Technical Staff, Applied Research — Sieve Location: San Francisco, CA (Onsite) Compensation: $150,000 – $350,000 base + 0.05% – 0.4% equity Visa Sponsorship: H-1B, O-1, OPT supported Experience Level: 2+ years Employment Type: Full-Time Headcount: 4 open seats About Sieve Sieve is the only AI research company exclusively focused on video data infrastructure and video intelligence. Their thesis: high-quality video training data is the key bottleneck limiting progress in video AI, robotics, AR/VR, generative media, and agentic systems. Sieve is building the infrastructure and datasets to solve that bottleneck. • Exabyte-scale video infrastructure, • Proprietary video understanding systems and internet-scale data processing, • Partners with top frontier AI labs and Fortune 100 enterprise customers, • Series A raised from Matrix Partners, Swift Ventures, Y Combinator, and AI Grant Core ownership includes: • High-performance video understanding building blocks, • Large-scale video processing pipelines, • Computer vision, audio processing, and text processing workflows, • Applied model optimization and pre/post-processing optimization, • Parallelized inference systems and pipeline orchestration, • Inference performance optimization and selective model fine-tuning, • Customer-driven problem decomposition, • End-to-end applied AI product deliveryRequirements, • 2+ years of computer vision or audio processing experience, • Strong Python engineering background, • Hands-on PyTorch or similar ML framework expertise, • Clean, maintainable production code, • Strong communication with customers and external stakeholders, • Passion for video and media technologies, • Product mindset — not research-only, • Ability to break customer problems into technical building blocks, • Willingness to work onsite in San FranciscoNice to Have, • Open source contributions or strong GitHub / portfolio projects, • Startup early-hire experience, • Applied research independence, • Video AI domain expertise, • Robotics experience, • Applied computer vision engineers, • Video AI specialists, • Robotics perception engineers, • Audio AI engineers, • Research engineers who ship production systems, • Startup technical builders with optimization depthThis Role Is NOT For, • Candidates with less than 2 years of relevant experience, • Profiles without independent research or technical ownership, • Those without a top-tier technical background, • Candidates with weak video or computer vision relevanceBenefits, • Competitive compensation and equity participation, • Health insurance, • Free lunch and dinnerInterview Process, • Application review, • Initial screen, • Technical chat with CTO, • Technical interview, • CEO conversation, • Onsite, • OfferLogistics, • Role is fully onsite in San Francisco — please only apply if you can commit to this

As a Data Scientist / Data Analyst / Data Science Specialist for Adidev Technologies Inc. Role: Data Scientist – Machine Learning Focus. Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB, PostgreSQL, Flask, streamlet and a good knowledge of data pipel

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace the___ to do your best work. Creating a career you love? It's Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process ___. As a machine learning intern in our Advance Technology Group at Pinterest, you will be exposed to a full spectrum of ML product development. The team focuses on developing cutting-edge technologies for Pinterest's visual understanding modules and recommender systems. You'll conduct research that can be applied across Pinterest engineering teams and engage in external collaborations and mentoring, while also having opportunities to deploy features to hundreds of millions of users or conduct research applicable for paper submissions. We offer a 12-week fall internship program remotely or in our San Francisco, Palo Alto, Seattle, or New York offices. Note to applicants: By applying to this role, you will be considered for multiple intern roles open across our various ML teams. Please only apply once within the USA or Canada as multiple applications may delay our recruitment process. Internships are 12 weeks paid from September 21 - December 11, 2026. Depending on the team, our fall internships will be located either remote or hybrid in San Francisco, Palo Alto, New York or Seattle offices. What you'll do: • Develop and launch new user features using unique internal datasets and ML techniques, especially in recommendation systems, computer vision, representation learning, generative AI, and responsible AI., • Gain hands-on experience with production ML systems, including algorithmic research, infrastructure, data engineering, training, inference, and product, to deliver innovative solutions. You will be exposed to full-stack production ML systems., • Leverage frontier AI tools and agents to accelerate engineering implementation, including prototyping and experimentation work., • Validate AI-generated outputs through testing, code review, and critical thinking, ensuring solutions are accurate, maintainable, secure, and aligned with team standards., • Use AI to better understand unfamiliar code, investigate bugs, and summarize technical context or documentation., • Contribute in cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems, • Write clean, efficient, and sustainable code, • Take proactive ownership over the completion and quality of your tasks and project with minimal guidance from your mentor, manager, and peers What we're looking for: • This role will be on our Visual Search or Applied Science teams. We are looking for candidates with experience in Computer Vision, Visual Search, User Understanding, Recommendation Systems, Reinforcement Learning, ML efficiency optimization, Generative AI, and LLMs., • Ability to legally work full time (40 hours/week) from September-December 2026, • Working towards a PhD degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field, • Mastery of at least one systems language (Java, C++, Python) and one ML framework (Tensorflow, Pytorch, MLFlow), • Proficiency with AI-native engineering, including the design of agent-friendly codebases., • High degree of autonomy in learning new agent-first development tools., • Strong critical thinking when working with AI-generated suggestions, with a clear approach to validating correctness, performance, security, and maintainability., • Comfort iterating on prompts, refining workflows, and adapting AI-assisted approaches based on the problem, context, and constraints., • Experience in research and in solving analytical problems, • Publications in machine learning, AI, data science, data analytics, statistics, or related technical fields, • Strong passion for research and for answering hard questions with research, • Meaningful Work: Contribute to projects that impact millions of users worldwide., • Mentorship: Learn from and be guided by experienced engineers and researchers in the field., • Growth and Development: Participate in professional development workshops and networking events to build your skills and connections. In-Office Requirement Statement: • We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection Information regarding the culture at Pinterest and benefits available for this position can be found___. US based applicants only The salary for this position is $12,100 monthly. #LI-HYBRID #LI-EB1 Our Commitment to Inclusion: Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete___for support.

About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, fueling the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we're amplifying access to high-quality data to drive progress toward Artificial General Intelligence (AGI). Building on our history of model evaluation with enterprise and government customers, we are expanding our capabilities to set new standards for both public and private evaluations. About This Role This role operates at the forefront of AI research and real-world implementation, with a strong focus on reasoning within large language models (LLMs). The ideal candidate will study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents. You will play a key role in shaping Scale's data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning. Success in this role requires a deep understanding of LLMs, planning algorithms, and novel approaches to agentic reasoning, as well as creativity in tackling challenges related to data generation, model interaction, and evaluation. You will contribute to impactful research on language model reasoning, collaborate with external researchers, and work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions. Ideally, you'd have: * Practical experience working with LLMs, with proficiency in frameworks like PyTorch, JAX, or TensorFlow. You should also be skilled at rapidly interpreting research literature and turning new ideas into working prototypes. * A track record of published research in top ML and NLP venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, CoLLM, etc.). * At least three years of experience solving complex ML challenges, either in a research setting or product development, particularly in areas related to LLM capabilities and reasoning. * Strong written and verbal communication skills, along with the ability to work effectively across teams. Nice to have: * Hands-on experience fine-tuning open-source LLMs or leading bespoke LLM fine-tuning projects using PyTorch/JAX. * Research and practical experience in building applications and evaluations related to LLM-based agents, including tool-use, text-to-SQL, browser agents, coding agents, and GUI agents. * Experience with agent frameworks such as OpenHands, Swarm, LangGraph, or similar. * Familiarity with advanced agentic reasoning techniques such as STaR and PLANSEARCH. * Proficiency in cloud-based ML development, with experience in AWS or GCP environments. Our research interviews are designed to assess candidates' ability to prototype and debug ML models, their depth of understanding in research concepts, and their alignment with our organizational culture. We do not conduct LeetCode-style problem-solving assessments. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$252,000—$315,000 USD PLEASE NOTE:Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's Pay Transparency provision. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

Who we are: Alignable is the largest online network of small business owners in North America, with over 10 million members. Our mission is to help entrepreneurs turn their relationships into a growth engine for their business. We're embarking on an exciting new chapter: transforming Alignable into the first relationship intelligence platform purpose-built for SMBs. Our vision is to become the system of record for SMB relationship data, using AI to help our members unlock new customers and opportunities through trusted referrals and warm introductions. At the center of this vision is our AI Networking Coach: an intelligent recommendation engine that continuously analyzes a member’s network and activity to surface the most valuable connections and actions. By turning relationships into actionable insights, Alignable empowers business owners to unlock the full potential of their professional networks and grow their businesses with confidence. If you're excited about the opportunity to shape the future of AI-powered products for millions of small businesses, we would love to hear from you. Why this role matters: As a Senior Product Manager at Alignable, you will be at the forefront of our AI transformation. Your work will shape how millions of small business owners leverage AI to connect, build relationships, and grow their businesses in the digital age. We're looking for a PM who has already been hands-on in leveraging AI to build innovative products. You've used tools like LLMs and code generation in your product work and understand deeply how the rapid evolution of AI is reshaping software development. In close collaboration with Product Design, Engineering, and Data Science, you will focus on infusing AI across our core offerings - from smart networking recommendations to conversational coaches to generative content creation. Your goal is to harness AI to deepen member engagement, satisfaction, and business growth. • Define the vision, strategy, and roadmap for AI-driven product initiatives in partnership with Product Design, Engineering, and Data Science, • Develop and launch AI-powered features in areas like intelligent recommendations, conversational AI, and content generation, • Collaborate with Product Design to craft intuitive, engaging user experiences that seamlessly integrate AI, • Partner with Data Science to productize AI/ML models using our stack (Python, TensorFlow, PyTorch, etc.), • Leverage LLMs, code generation, and emerging AI technologies to rapidly prototype and launch new capabilities, • Design experiments and interpret data to quantify the impact of AI products and drive iteration, • Influence key stakeholders across Product, Marketing, Sales, and Customer Success to align on AI priorities, • Evangelize AI best practices and contribute to thought leadership, • Champion responsible AI practices around transparency, fairness, privacy, and ethics, • Successful launch of AI-powered products that demonstrably improve engagement, revenue, and other key metrics, • Seamless integration of AI into core platform experiences, • Productive relationships with technical and non-technical partners, • Tangible contributions to Alignable's evolution into an AI-first organization, • Emerging thought leadership in AI product development for SMBs, • 5+ years of product management experience, with 2+ years building AI/ML-driven products preferred, • Hands-on experience leveraging LLMs, code generation, and productizing ML models, • Understanding of the evolving AI/ML landscape and its implications for product development, • Track record of launching successful 0-to-1 products, • Strong technical fluency and ability to partner effectively with AI/ML and Engineering teams, • Excellent analytical skills and experience with experiment-driven product development, • Entrepreneurial mindset and comfort with ambiguity, • Passion for helping small businesses succeed through technology, • Impact & Mission: Help millions of small businesses grow through trusted relationships while owning a pivotal moment in Alignable’s evolution toward AI-powered, product-led sales., • Team & Environment: Partner with a founder-led, cross-functional leadership team with deep experience in SMB, SaaS, and growth-driven businesses., • Compensation & Benefits: Competitive salary, meaningful equity, flexible work, comprehensive benefits, and long-term ownership upside.

About Cleerly We’re Cleerly – a healthcare company that’s revolutionizing how heart disease is diagnosed, treated, and tracked. We were founded in 2017 by one of the world’s leading cardiologists and are a growing team of world-class engineering, operations, medical affairs, marketing, and sales leaders. We raised $223M in Series C funding in 2022 which has enabled rapid growth and continued support of our mission. In December 2024 we received an additional $106M in a Series C extension funding. Most of our teams work remotely and have access to our offices in Denver, Colorado, New, York, New York, Dallas, Texas, and Lisbon, Portugal with some roles requiring you to be on-site in a location. Cleerly has created a new standard of care for heart disease through value-based, AI-driven precision diagnostic solutions with the goal of helping prevent heart attacks. Our technology goes beyond traditional measures of heart disease by enabling comprehensive quantification and characterization of atherosclerosis, or plaque buildup, in each of the heart arteries. Cleerly’s solutions are supported by more than a decade of performing some of the world’s largest clinical trials to identify important findings beyond symptoms that increase a person’s risk of heart attacks. At Cleerly, we collaborate digitally and use a wide variety of systems. Our people use Google Workspace (GMail, Drive, Docs, Sheets, Slides), Slack, Confluence/Jira, and Zoom Video, prior experience in these areas is a plus. Role or department specific technology needs may vary and will be listed as requirements in the job description. While we are mostly a remote company, travel is required for some team meetings and cross function projects typically once per month or once per quarter, for some roles like sales or external facing roles travel could be up to 90% of the time. About the Opportunity We're seeking a Software Engineer 3 to drive key technical initiatives across our computational imaging pipeline. In this high-impact role, you'll be part of the team owning the complex systems responsible for deploying, scaling, and monitoring our regulated AI algorithms end-to-end. You will influence the architecture of our system, ensuring our solutions meet medical standards for quality and performance, while mentoring other engineers and helping shape our technical culture. About the Team You will join our expert Computational Imaging team, where we develop sophisticated algorithms to enhance and improve medical imaging. We are focused on improving the quality and clinical value of medical images, creating powerful, extra software components that correct artifacts, standardize data, and ensure the utmost precision before the final analysis. Our work is essential for elevating the reliability and accuracy of Cleerly’s regulated products. Responsibilities • Build and deploy scalable AI services and computational imaging pipelines to production, ensuring robust, high-availability infrastructure for our machine learning algorithms., • Contribute to the system architecture's design and make pragmatic trade-offs that balance performance, security, and maintainability., • Own full lifecycle delivery of complex features, from architectural planning and API design to implementation and post-release observability., • Support the high availability and observability of our services; improve alerting, logging, and incident response across the stack., • Uphold strong engineering standards via code reviews, technical mentorship, and design documentation., • Collaborate closely across AI and engineering to reduce knowledge silos and ensure continuity in critical systems through cross-training and documentation., • Implement robust testing mechanism and validation strategies to ensure compliance with our Quality Management System and regulatory standards Requirements • Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field (or equivalent experience)., • 5–8 years of software engineering experience, with expertise in AI production systems (Python, PyTorch) and data services (SQL, Postgres, NoSQL, Redis or similar)., • Demonstrable capability in designing, implementing, and securing RESTful web services, • Experience in MLOps orchestration and cloud deployment (Docker, Kubernetes)., • Experience with AWS, GitHub, and continuous integration pipelines, • Proven track record of delivering scalable systems in production environments., • Strong systems thinking with the ability to evaluate tradeoffs in scalability, reliability, and maintainability., • Experience designing for observability and operational excellence (e.g., logs, alerts, dashboards, runbooks)., • Comfortable operating in ambiguity and driving clarity across product, engineering, and business stakeholders. Preferred: • Experience designing and optimizing end-to-end medical imaging pipelines in a production environment and familiarity with HIPAA/HITRUST security requirements., • Hands-on experience with Computer Vision and Deep Learning techniques used for medical image processing. OUR COMPANY IS AN EQUAL OPPORTUNITY EMPLOYER. We do not discriminate on the basis of race, color, national origin, ancestry, citizenship status, protected veteran status, religion, physical or mental disability, marital status, sex, sexual orientation, gender identity or expression, age, or any other basis protected by law, ordinance, or regulation. Job duties, activities, and responsibilities are subject to change by our company. The base salary range for this role varies by location and is aligned to market benchmarks. • Candidates located in higher-cost labor markets, including California, Washington, New York, New Jersey, Connecticut, Massachusetts, and Washington, DC represent the middle to high end of the range, while candidates located in all other U.S. locations represent the low to middle end of the range., • Final compensation is determined based on location, experience, skills, and internal equity. This role is eligible for a 15% target annual bonus, resulting in the following base salary and Total Target Compensation (TTC) ranges: • Base Salary: $129,000 - $152,000, • TTC: $142,000 - $168,000 *Total Target Compensation (TTC): Total Cash Compensation (including base pay, variable pay, commission, bonuses, etc.) Additionally, stock options, paid benefits, and employee perks are part of your total rewards. Working at Cleerly takes HEART. Discover our Core Values: • H: Humility- be a servant leader, • E: Excellence- deliver world-changing results, • A: Accountability- do what you say; expect the same from others, • R: Remarkable- inspire & innovate with impact, • T: Teamwork- together we win Don’t meet 100 percent of the qualifications? Apply anyway and help us diversify our candidate pool and workforce. We value experience, whether gained formally or informally on the job or through other experiences. Job duties, activities and responsibilities are subject to change by our company. OUR COMPANY IS AN EQUAL OPPORTUNITY EMPLOYER. We do not discriminate on the basis of race, color, national origin, ancestry, citizenship status, protected veteran status, religion, physical or mental disability, marital status, sex, sexual orientation, gender identity or expression, age, or any other basis protected by law, ordinance, or regulation. For more information see our Privacy Policy (___. All official emails will come from @cleerlyhealth.com email accounts. #Cleerly

Octave is a modern behavioral health practice creating a new standard for care delivery that’s both high-quality and accessible. With in-person and virtual clinics in multiple states, the company offers evidence-based individual, couples, and family therapy, while pioneering relationships with payers to make care more affordable through insurance. By raising the bar on how care is delivered and how providers are supported, we are building a sustainable system that values equity, affordability, and effectiveness. We’re looking for a Sr. Data Engineer with strong data platform experience to help evolve our modern data stack and contribute to the foundation of our emerging AI and ML platform. This role sits at the intersection of data engineering, platform architecture and machine learning enablement and will bring high-quality, scalable, and ethical AI into real-world use. You will partner closely with data scientists, analysts, and product managers to ensure our platform supports reliable data pipelines, scalable analytics, and production ready machine learning systems in addition to defining new architecture, best practices, and patterns for fellow engineers to inherit. The ideal candidate is both a systems thinker and a hands-on builder who thrives in evolving environments and is passionate about creating reliable data infrastructure that enables peers and partner teams to move faster with data. • Design, build, and maintain scalable systems for ingestion, transformation, and storage of data, with a focus on testing and observability., • Implement frameworks, tooling, and automation to safely increase development velocity., • Develop foundational end-to-end AI/ML workflows from (1) source ingestion and preparation, (2) training and tuning, (3) experimentation and productionization, and (4) downstream systems integration (EHR modules, micro-services, dashboards)., • Support iterative model development and production operations and observability (accuracy, drift, bias, fairness, reproducibility)., • Contribute to a culture of continuous improvement, knowledge-sharing and mentoring of peer engineers., • Bachelor’s degree (or equivalent) in Computer Science, Data Science, Statistics, Engineering or a related field., • 5+ years of experience in data engineering, platform engineering, or ML engineering., • Experience working with major cloud data platforms and tools:, • Preferred experience:, • Healthcare, behavioral health, EHR systems, and/or regulated industries., • Specific expertise with: AWS/GCP, dbt, AirflowAirbyte, Redshift/BigQuery., • Proficiency in SQL and Python with strong familiarity towards modern data engineering frameworks, infrastructure, and tooling., • Proficiency with data ops best practices, monitoring, pipeline automation, and CI/CD., • Knowledge of modern compute and ML frameworks/libraries (i.e., Spark, TensorFlow, PyTorch, scikit-learn)., • Ability to build production APIs and services, inclusive of MCP servers that expose internal data/services to LLMs., • A collaborative mindset, dependable execution, drive to reflect and improve, and humility to ask questions and learn. The below values drive our day-to-day operations. • We’re human beings first. We operate with empathy and kindness – with our clients, with our collaborators, and with ourselves., • People deserve better than status quo. We’re willing to tackle the intractable problems, no matter how big, because someone should. We ask big questions, we craft big solutions, and we challenge ourselves and others to make it happen., • No bystanders. No stars. No tourists. Each person has been selected to be here, and with that comes a responsibility to bring your expertise, share your ideas, and help make this company better., • Partnership paves the path ahead. We don’t operate in a silo, internally or externally. To transform the system, we believe in working with others to create something bigger, better, and stronger., • Quality is crucial at scale. Quality is core to our business, and we refuse to sacrifice it as we grow., • Progress is a process. In the pursuit of progress, we iterate, reflect, learn, adjust – and always leave things better than we found them., • There are people behind every data point. We recognize that numbers tell only one part of the story, and we also do the work to understand impacts at the individual level., • Prolonged periods sitting at a desk and working on a computer., • Must be able to frequently communicate with others through virtual meeting applications such as Zoom and Google Meet., • Must be able to observe and communicate information on company provided laptop., • Move up to 10 pounds on occasion., • Must be eligible to work in the United States without sponsorship now or in the future. Octave is committed to pay equity. To maintain our commitment to pay equity, Octave will follow Pay Transparency regulations on all open job postings. Current Pay Transparency laws require companies to include a position's salary or hourly wage range (not including bonuses or equity-based compensation) in any internal or external job posting. This requirement extends to job postings published by a third party at an employer's request. Octave will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with Octave’s legal duty to furnish information. Starting pay for qualified applicants will depend on a combination of job-related factors, which may include education, training, experience, location, business needs, or market demands. The expected salary range for this role is set forth below and this range may be modified in the future. The salary range for Geo 1 (all states, excluding those in Geo 2 or Geo 3, and D.C.) is $142,600 - $153,100. The salary range for Geo 2 (CO, HI, MD, RI) is $156,900 - $168,400. The salary range for Geo 3 (AK, CA, CT, MA, NJ, NY, WA) is $164,000 - $176,000. All Geos are eligible for equity in the form of stock options. Additionally, this position is eligible for the following benefits: company sponsored life insurance, disability and AD&D plans. Voluntary benefits such as 401k retirement, medical, dental, vision, FSA, HSA, dependent care and commuter/parking options are also available. Octave offers generous Paid Time Off as well as paid parental leave benefits. This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without notice. As part of our hiring process, we may use technology tools, including AI-supported systems, to assist with reviewing applications or documenting interviews. These tools are designed to support our team, not replace human judgment, and final hiring decisions are always made by our team. This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without notice. Application Instructions: Please complete the following application. Please note that the U.S. Equal Opportunity Employment Information questions below are used for the purposes of EEOC reporting and are optional to complete. Octave is unable to change these questions and we acknowledge that many of the U.S. Equal Opportunity Employment Information questions are not inclusive or affirming of all aspects of cultural identity. Octave is committed to an inclusive workplace environment, and this information will not inform how we approach hiring or employment.

Reddit is a community of communities. It’s built on shared interests, passion, and trust and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 101M+ daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit ___. The Notifications Relevance Team focuses on delivering the right content to the right user at the right time through push, email, and in-app notifications. Our systems and algorithms operate on the world's largest corpus of human conversation, connecting Redditors with what matters - whether it’s recommending similar posts and subreddits, surfacing conversations they’ll care about, or introducing communities they didn’t know they needed. We are looking for an Engineering Manager to lead our Notifications Relevance team, shaping the future of Notifications at Reddit. In this role, you will lead a team of machine learning engineers dedicated to advancing our current Notifications Relevance systems. This is a high-impact team driving DAU growth and long-term user retention by connecting users to what matters most to them. If applying ML / AI in production to improve the relevance of Reddit Notifications excites you, then you’ve found the right place. What You’ll Do • Lead the team that architects and designs notifications relevance at Reddit., • Guide team on holistic, adaptive systems covering budgeting optimization, candidate retrieval, and ranking., • Work with ML engineers to design, implement, and optimize machine-learning models that drive personalization and user re-engagement., • Participate in the full development cycle: design, develop, QA, experiment, analyze, and deploy., • Build and maintain a diverse team that can collaborate across disciplines to find technical solutions to complex challenges., • Serve as a thought partner to product and upper management to ensure your team’s plans align with company goals., • Communicate your team’s work and set expectations with cross-functional stakeholders., • Help your engineers identify career goals and create development plans to achieve them., • Constantly seek opportunities to push your engineers & managers outside their comfort zone and turn followers into leaders. You Have: • 2+ years of experience building and managing engineering teams., • 5+ years of experience as a Machine Learning Engineer or Software Engineer working on large-scale machine learning systems., • Deep understanding of building and deploying large-scale recommender systems (retrieval + ranking) in production., • Hands-on experience working with deep learning models, sequential features and real-time systems., • Experience with distributed training and inference using tools like Ray, PyTorch Distributed, or similar., • Familiarity with reinforcement learning or multi-objective optimization in recommendation systems., • Entrepreneurial and self-directed, innovative, results-oriented, biased towards action in fast-paced environments., • Able to communicate and discuss complex topics with technical and non-technical audiences., • Able to tackle ambiguous and undefined problems. Benefits: • Comprehensive Healthcare Benefits and Income Replacement Programs, • 401k Match, • Family Planning Support, • Gender-Affirming Care, • Mental Health & Coaching Benefits, • Flexible Vacation & Reddit Global Days off, • Generous paid Parental Leave, • Paid Volunteer time off Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit ___. To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base pay range for this position is: $230,000 - $322,000 USD In select roles and locations, the interviews will be recorded, and transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our ___. Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

As a Software Engineer on the Machine Learning Infrastructure team, you will build the "Operating System" for our large-scale GPU clusters. You will architect a high-performance training platform that handles the immense complexity of multi-thousand GPU workloads, ensuring every cycle is used efficiently. Your work directly determines the velocity at which our researchers can train and iterate on the world's most advanced models. The ideal candidate is a systems expert who thrives on solving the orchestration, networking, and reliability challenges that emerge at massive scale. You will partner closely with researchers to build a seamless, resilient environment that transforms raw compute into breakthrough AI. • Architect and scale a multi-tenant orchestration layer that abstracts away the complexity of GPU clusters, ensuring high utilization and seamless job recovery., • Design and implement scheduling primitives to optimize the lifecycle of training jobs., • Develop deep observability and automated health-checking into the training stack to proactively identify and isolate hardware failures, • Evaluate and integrate emerging technologies in the CNCF and AI ecosystem (e.g. Ray, Kueue), making data-driven build vs. buy decisions that balance velocity with long-term maintainability., • Work closely with Finance and Procurement teams to drive our capacity planning process., • Participate in our team's on call process to ensure the availability of our services., • Own projects end-to-end, from requirements, scoping, design, to implementation, in a highly collaborative and cross-functional environment., • 5+ years of experience in backend or infrastructure engineering, with at least 2 years focused on orchestrating ML workloads at scale (100+ GPU nodes)., • Strong programming skills in one or more languages (e.g. Python, Go, Rust, C++), • Experience with complex compute management systems that cover queueing, quotas, preemption, and gang scheduling., • Experience with distributed training infrastructure, such as EFA, Infiniband, and topology-aware scheduling., • Experience with distributed storage systems (e.g. Lustre, S3) as they relate to training throughput, • Expert-level knowledge of Kubernetes internals (Custom Resources, Operators, Admission Controllers) and how they interact with device plugins for specialized hardware., • Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform)., • Proven ability to solve complex problems and work independently in fast-moving environments., • Experience with distributed training techniques such as DeepSpeed, FSDP, etc., • Experience with the NVIDIA software and hardware stack (CUDA, NCCL), • Experience with PyTorch About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's Pay Transparency provision. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

Job Type: Term (Fixed Term) Job Description Overview RAND's ___, part of the Global and Emerging Risks (GER) Division conducts cutting-edge research on transformative, high-impact technologies-including artificial intelligence and biotechnology-to shape policies that protect global security and advance the public good. Your work will address key questions related to securing AI systems, understanding their cyber capabilities, and examining their policy implications. You will be responsible for leading complex projects that span technical research, policy analysis, and infrastructure development. For example, you might lead projects to develop AI-specific threat models, build software tools for AI cyber capability evaluations, or identify critical areas for new security R&D. Your work will inform analysis delivered to senior government and industry leaders. You will communicate the results of your work to both technical and non-technical audiences through quick-turnaround policy briefs and detailed written research products. A recent example of one of our research products is the ___ report, which explored protecting frontier AI models from theft and misuse. This position is structured as a three-year appointment with options to renew and explore opportunities for longer-term employment at RAND thereafter. RAND's reputation for excellence is built on our commitment to high-quality, rigorous analysis and objectivity. As an Associate AI Security Resident, you'll maintain that excellence while engaging with some of the most pressing challenges of our time. Qualifications All research positions at RAND require excellent analytic skills; the ability to communicate clearly and effectively, both orally and in writing; the ability to work effectively as a member of a multi-disciplinary team; and a strong commitment to RAND's core values of quality and objectivity. Required: * Technical experience in security engineering, software engineering, firmware engineering, hardware engineering, or related fields * Technical management experience, including leading cross-functional teams, managing project budgets, and mentoring and developing team members * Demonstrated ability to successfully lead complex projects to completion * Proficiency in Python, Java, C/C++, or other popular programming languages * Ability to develop rigorous and comprehensive ___ and identify potential system vulnerabilities * Excellent communication skills, both written and verbal, tailored to technical and non-technical audiences * Ability to reason about policy options given different technical considerations * Ability to work effectively in a collaborative, multidisciplinary environment * Fluency with MS Office suite Preferred: * Graduate of the Computer Network Operations Development Program (CNODP), Remote Interactive Operator Training (RIOT), Future Operator Readiness Growth and Enrichment (FORGE), or equivalent experience * Experience with red team operations or offensive cyber capabilities development * Understanding of ___ (APT) tactics, techniques, and procedures (TTPs) and experience with defending against them * Ability to think creatively about offensive and/or defensive techniques and strategies, beyond compliance with existing regulations * Familiarity with U.S. cybersecurity agencies, authorities, and policy development processes * Experience working in or with government on cybersecurity policy * Experience with advising non-technical stakeholders on security topics * Familiarity with the AI/ML hardware stack (e.g., GPUs, TPUs, data center design) * Familiarity with the AI/ML software stack (e.g., CUDA, PyTorch, TensorFlow, Ray) * Experience working on AI research, ML model training, or model deployment * Experience with securing AI systems Education Requirements RAND is hiring multiple Visiting AI Security Residents at associate I and associate II levels of experience. Minimum education requirements at the associate I level include: A BS in Computer Science, Computer Engineering, Electrical Engineering, Cybersecurity, Information Security, Information Technology, Mathematics, Applied Mathematics, Physics, Applied Physics, Engineering Physics, Artificial Intelligence, Machine Learning, Engineering and Public Policy, Technology and Policy, National Security Policy, Policy Analysis, Political Science, International Relations, or similar AND 1 year AI-focused real-world experience is required. OR A Master's degree in the fields listed above is required. Security Clearance Ability to obtain and maintain a U.S. government clearance is preferred but not required. Location We are hiring for this position in San Francisco, CA, Washington, DC; Santa Monica, CA; Pittsburgh, PA; and Boston, MA. We offer a hybrid work arrangement, combining work from home and on-site options. Fully remote work within the US, along with US visa support, will also be considered. Writing or Code Sample Either a writing sample or a code sample is required for this position. This sample can use a recent, previously written paper or technical report (e.g., journal article, master's thesis or paper written for coursework, research project, technical analysis, briefings), or source code showing technical expertise in relevant domains. Term This position is a three-year term appointment with a possibility of renewal, alongside options for longer term employment. Salary Range: Visiting Technical Associate I = $90,400 - $134,400 Visiting Technical Associate II = $121,700 - $176,500 RAND considers a variety of factors when formulating an offer, including but not limited to, the specific role and associated responsibilities; a candidate's work experience, education/training, skills, expertise; and internal equity.Successful candidates will be offered employment in a specific title, as determined by the candidate's education and experience. The salary range includes base pay plus RAND's sabbatic pay (which provides additional compensation above base pay when vacation is taken). In addition, RAND provides strong benefits including health insurance coverage, life and disability insurance, savings plan, paid time-off and more. #LI-DNI Equal Opportunity Employer

Scale's ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale's ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! • Build, profile and optimize our training and inference framework, • Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation, • Research and integrate state-of-the-art technologies to optimize our ML system, • Strong excitement about system optimization, • Experience with multi-node LLM training and inference, • Experience with developing large-scale distributed ML systems, • Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc., • Strong written and verbal communication skills and the ability tooperate in a cross functional team environment, • Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$189,600—$237,000 USD PLEASE NOTE:Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's Pay Transparency provision. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

Lead applied ML engineering on Scale's Applied ML team, powering data infrastructure for leading agentic LLMs (ChatGPT, Gemini, Llama). You will build scalable multi-agent systems to validate agentic reasoning and behaviors, scale human expertise, and drive research into real-world agent reliability failures despite strong benchmarks, shipping production fixes. Ideal for exceptional engineers with deep research rigor and a relentless focus on practical, high-impact systems. You will iterate rapidly with data, leverage AI tools to accelerate development, and collaborate tightly across engineering, product, and research. If you excel at turning frontier agent research into reliable deployed systems, we want to hear from you. You will: • Build and deploy multi-agent systems for agentic reasoning validation, • Develop pipelines to detect errors and scale human judgment, • Combine classical ML, LLMs, and multi-agent techniques for reliability, • Lead research into agent failure modes and ship fixes, • Use AI tools to speed prototyping and iteration, • Build data-driven evaluations and deploy rapid improvements, • PhD or MSc in Computer Science, Mathematics, Statistics, or related field, • 3+ years shipping scaled production ML systems, • Demonstrated real-world impact, • Mastery of PyTorch, TensorFlow, JAX, or scikit-learn, • Deep expertise in agentic LLMs and multi-agent systems, • Strong software engineering and microservices (AWS/GCP), • Rapid, data-driven iteration, • Proficiency using AI tools to accelerate work, • Strong research depth with practical bias, • Experience prototyping agent evaluation/reliability systems, • Human-in-the-loop or annotation pipeline work, • Open-source contributions in agents, evaluation, or alignment About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's Pay Transparency provision. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

Welcome to Planet. We believe in using space to help life on Earth. Planet designs, builds, and operates the largest constellation of imaging satellites in history. This constellation delivers an unprecedented dataset of empirical information via a revolutionary cloud-based platform to authoritative figures in commercial, environmental, and humanitarian sectors. We are both a space company and data company all rolled into one. Customers and users across the globe use Planet's data to develop new technologies, drive revenue, power research, and solve our world's toughest obstacles. As we control every component of hardware design, manufacturing, data processing, and software engineering, our office is a truly inspiring mix of experts from a variety of domains. We have a people-centric approach toward culture and community and we strive to iterate in a way that puts our team members first and prepares our company for growth. Join Planet and be a part of our mission to change the way people see the world. Planet is a global company with employees working remotely world wide and joining us from offices in San Francisco, Washington DC, Germany, Austria, Slovenia, and The Netherlands. About the Role: We are seeking a highly motivated Visiting Scientist (Postdoctoral Researcher) to join our AI Research (AIR) team for a one-year residency. In this role, you will work directly with Dr. Mirela Tulbure during her sabbatical at Planet to develop our proprietary geospatial foundation models (GFMs). While Planet has historically leveraged external models, we are now focused on building in-house models specifically trained on our unique imagery. As a postdoctoral researcher, you will be the primary technical engine behind creating temporally dense embeddings that capture the dynamic and ephemeral nature of our planet-such as rapid flooding and disaster impacts. You will collaborate with "Planeteers" across data pipelines and analytics to bridge the gap between academic research and operational AI/ML solutions. Impact You'll Own: • GFM Implementation: Contribute to the design and training of a foundation model specifically optimized for Planet imagery, focusing on the integration of time-series data., • Technical Benchmarking: Execute the systematic evaluation of existing GFM architectures (e.g., TerraMind, Prithvi, Clay) against PlanetScope data to identify performance bottlenecks and transferability., • Prototype Development: Build and test workflows for detecting short-lived events, such as floods and fires, using high-cadence embeddings., • Multi-Sensor Data Fusion: Develop methods to integrate PlanetScope with Sentinel-1 SAR and other commercial datasets to maintain time-series continuity under cloud cover., • Research to Production: Work closely with Planet's research scientists to transition experimental prototypes into scalable, operational products., • Academic Foundation: A recently completed PhD in Geospatial Analytics, Computer Science, Remote Sensing, or a related field., • Research Track Record: Demonstrated experience in building AI-based models for environmental change or satellite image analysis., • AI/ML Fluency: Hands-on experience with foundation models, contrastive learning, and deep learning frameworks (PyTorch/TensorFlow)., • Advanced Technical Stack: Expert-level Python skills and proficiency with the geospatial scientific stack (e.g., xarray, Dask, Rasterio, GeoPandas)., • Data Engineering Aptitude: Experience building automated pipelines for preprocessing and labeling planetary-scale datasets., • Specialized Domain Knowledge: Prior research in flood-extent mapping, water dynamics, or disaster response., • GFM Fine-Tuning: Direct experience fine-tuning or modifying specific GFM architectures like TerraMind, Prithvi, or Clay. Application Deadline: August 12, 2026 by 11:59p / 23:59 CET (Central European Time) Benefits While Working at Planet: These offerings are dependent on employment type and geographical location, based upon applicable law or company policy. • Comprehensive Medical, Dental, and Vision plans, • Health Savings Account (HSA) with a company contribution, • Generous Paid Time Off in addition to holidays and company-wide days off, • 16 Weeks of Paid Parental Leave, • Wellness Program and Employee Assistance Program (EAP), • Home Office Reimbursement, • Monthly Phone and Internet Reimbursement, • Tuition Reimbursement and access to LinkedIn Learning, • Equity, • Commuter Benefits (if local to an office) The US base salary range for this full-time position at the commencement of employment is listed below. Additionally, this role might be eligible for discretionary short-term and long-term incentives (bonus and equity). The final salary range is determined by job related experience, skills and location. The range displays our typical hiring range for new hire salaries in US locations only. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. San Francisco Salary Range$144,500—$180,600 USD San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Why we care so much about Belonging. We're dedicated to helping the whole Planet, and to do that we must strive to represent all of it within each of our offices and on all of our teams. That's why Planet is guided by an ultimate north star of Belonging-dreaming big as we approach our ongoing work. If this job intrigues you, but you're thinking you might not have all the qualifications, please... do apply! At Planet, we are looking for well-rounded people from around the world who can contribute to more ways than just what is listed in this job description. We don't just fill positions, we aspire to fulfill people's careers, most excited about folks who are motivated by our underlying humanitarian efforts. We are a few orbits around the sun before we get to where we want to be, so we hope you're excited to come along for the ride. EEO statement: Planet is committed to building a community where everyone belongs and we invite people from all backgrounds to apply. Planet is an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. ___ Accommodations: Planet is an inclusive community and we know that everyone has their own needs. If you have a disability or special need that requires accommodation during the hiring process, please reach out to or contact your recruiter with your request. Your message will be confidential and we will be happy to assist you. Privacy Policy: By clicking "Apply Now" at the top of this job posting, I acknowledge that I have read the ___, and hereby consent to the collection, processing, use, and storage of my personal information as described therein. Privacy Policy (European Applicants): By clicking "Apply Now" at the top of this job posting, I acknowledge that I have read the ___, and hereby consent to the collection, processing, use, and storage of my personal information as described therein. AI in Our Interviewing Process: Planet is committed to providing an exceptional interview experience for all candidates. We are currently exploring AI interviewing technologies to better focus on candidates and less on trying to capture notes. As such, with the candidate's consent, select interviews may be recorded and include a Planet AI Notetaker for transcription and summarization purposes. Should an interview involve use of AI interview technologies, the candidate will receive notification and have the ability to opt out both in advance and/or real-time. Opting out will not affect one's candidacy. Candidate AI Policy: Planet embraces Artificial Intelligence (AI) tools, and we encourage its responsible use. We understand that candidates may use various resources, including AI tools, to prepare for interviews and assessments. However, during any live interview stage or when actively completing assessments for this position, the use of AI tools-e.g. Large Language Models (LLMs), deep fake technology, etc.-is strictly prohibited unless explicitly prompted by an interviewer or assessment instructions. If you are unsure about acceptable use, please contact your recruiter for clarification. If an AI tool or similar technology is desired as an accommodation, please contact with your request for assistance. Your message will be confidential, and we will be happy to assist you. Violation of this policy may result in disqualification of your application.

Scale AI is the data engine for the entire AI industry. Our mission is to accelerate the development of AI applications by providing organizations with the high-quality data they need. The Physical AI team at Scale is focused on the next frontier: building general AI that can reason and act in the physical world. By leveraging Scale's massive data infrastructure, we are helping frontier labs build Foundation Models for Physical AI that will redefine the future of automation. As the Technical Lead Manager (TLM) for the Physical AI team of Scale, you will bridge the gap between cutting-edge Machine Learning research and physical robot deployment. You will lead a high-performing team of Research Engineers while remaining a hands-on technical contributor (~60% of your time). Your primary focus will be the development and evaluation of Large-Scale Foundation Models (e.g VLAs, World models) that allow robots and AVs to generalize across diverse tasks, environments, and morphologies. • Model Scaling: Direct research into scaling laws for Physical AI, determining how to best utilize massive datasets for pre-training and fine-tuning generalist policies., • VLA and World model development: Develop novel methods for developing and evaluating models, including new Physical AI industry benchmarks, • Hands-on Modeling: Actively write code to implement, train and test SOTA architectures. Conduct research on Physical AI data collection, cross-embodiment training, and policy fine-tuning., • Data Strategy: Collaborate with internal labeling teams to design "robotic-native" data pipelines, including the use of VLMs for automated trajectory annotation and data synthesis., • Collaborate closely with customers to drive the industry forward in using Scale data, • Mentorship: Lead and grow a team of 4-6 elite Physical AI researchers, fostering a culture of high-velocity experimentation and rigorous evaluation., • Paper-to-Product: Translate the latest research from NeurIPS, ICRA, and CVPR into production-ready features for Scale's Physical AI partners., • Cross-functional Alignment: Work with cross-functional teams (e.g Product and Operations) to bring our research breakthroughs into production., • Deep Learning Mastery: Expert-level proficiency in PyTorch, with deep knowledge of Transformer architectures, Attention mechanisms, and Self-Supervised Learning., • VLM/VLA Experience: Proven track record of working with Vision-Language Models (e.g., CLIP, PaLM-E) and adapting them for spatial reasoning or embodied tasks., • Generative AI: Experience with Diffusion Models for sequence generation or Generative World Models for predictive modeling., • Embodied AI: Strong understanding of Physical AI stack, including imitation learning, reinforcement learning (RL), and multi-modal sensor fusion., • Infrastructure: Experience with large-scale distributed training across GPU clusters and high-performance data loading., • Leadership: 1+ years of experience leading technical teams or projects in a research-intensive environment., • Publication Record: First-author publications at top-tier AI/ML conferences (NeurIPS, CVPR, ICRA, CoRL)., • Hardware Generalization: Experience building models that work across different robot types (arms, mobile bases, humanoids). About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's Pay Transparency provision. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale's ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! • Build, profile and optimize our training and inference framework., • Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation., • Research and integrate state-of-the-art technologies to optimize our ML system., • Passionate about system optimization, • Experience with multi-node LLM training and inference, • Experience with developing large-scale distributed ML systems, • Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc., • Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc., • Strong written and verbal communication skills to operate in a cross functional team environment., • Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$264,800—$331,000 USD PLEASE NOTE:Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's Pay Transparency provision. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

The goal of a Senior Machine Learning Engineer at Scale is to leverage techniques in the fields of generative AI, computer vision, reinforcement learning, and agentic AI to improve Scale's products and customer experience in production environments. Our machine learning engineers take advantage of robust internal infrastructure and unique access to massive datasets to deliver improvements to our customers. Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like ___ and ___. Our work spans multiple modalities, with a strong focus on both large language models and computer vision. On the LLM side, we are developing agentic systems that help solve complex operational and planning challenges for government partners. This includes building agent frameworks that integrate with custom retrieval pipelines and production APIs, as well as evaluation tools to benchmark and refine agent behavior. We're also advancing research in areas like reinforcement learning for agentic LLMs, with successful deployment into real-world operational environments. On the computer vision front, we're training advanced models to increase labeling throughput and automate perception tasks. Our efforts include building large-scale fine-tuning pipelines, training models across multiple modalities, and developing generalizable vision foundation models to support a wide range of defense applications. • Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers, • Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics, • Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines, • Work with massive datasets to develop both generic models as well as fine tune models for specific products, • Build scalable machine learning infrastructure to automate and optimize our ML services, • Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations, • Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment, • Comfortable with light travel (approximately 10%) for customer interaction and team needs, • This role will require an active security clearance or the ability to obtain a security clearance, • Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment, • Solid background in algorithms, data structures, and object-oriented programming, • Strong programing skills in Python, experience in Tensorflow or PyTorch, • Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization, • Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments, • Experience with computer vision, generative AI models, large language models, or agentic systems About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's Pay Transparency provision. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

Senior Machine Learning Engineer - Model Evaluations, Public Sector The Public Sector ML team at Scale deploys advanced AI systems-including LLMs, agentic models, and multimodal pipelines-into mission-critical government environments. We build evaluation frameworks that ensure these models operate reliably, safely, and effectively under real-world constraints. As an ML Engineer, you will design, implement, and scale automated evaluation pipelines that help customers trust and operationalize advanced AI systems across defense, intelligence, and federal missions. You will: • Develop and maintain automated evaluation pipelines for ML models across functional, performance, robustness, and safety metrics, including LLM-judge-based evaluations., • Design test datasets and benchmarks to measure generalization, bias, explainability, and failure modes., • Build evaluation frameworks for LLM agents, including infrastructure for scenario-based and environment-based testing., • Conduct comparative analyses of model architectures, training procedures, and evaluation outcomes., • Implement tools for continuous monitoring, regression testing, and quality assurance for ML systems., • Design and execute stress tests and red-teaming workflows to uncover vulnerabilities and edge cases., • Collaborate with operations teams and subject matter experts to produce high-quality evaluation datasets. Ideally you'd have: • Experience in computer vision, deep learning, reinforcement learning, or NLP in production settings., • Strong programming skills in Python; experience with TensorFlow or PyTorch., • Background in algorithms, data structures, and object-oriented programming., • Experience with LLM pipelines, simulation environments, or automated evaluation systems., • Graduate degree in CS, ML, or AI., • Cloud experience (AWS, GCP) and model deployment experience., • Experience with LLM evaluation, CV robustness, or RL validation., • Knowledge of interpretability, adversarial robustness, or AI safety frameworks., • Familiarity with ML evaluation frameworks and agentic model design. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's Pay Transparency provision. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

Octane® is revolutionizing recreational purchases by delivering a seamless, end-to-end digital buying experience. We connect people with their passions by combining cutting-edge technology and innovative risk strategies to make lifestyle purchases - like powersports vehicles, RVs, and OPE - fast, easy, and accessible. Octane adds value throughout the customer journey: inspiring enthusiasts with our editorial brands, including Cycle World® and UTV Driver®, instantly prequalifying consumers for financing online, routing customers to dealerships for an easy closing, and supporting customers throughout their loan with superior loan servicing. Founded in 2014, we’re a company with 550+ employees and over 30 OEM and 4,000 dealer partners. At Octane, we’re building innovative technology solutions that power smarter, faster, and more efficient decision-making. We are seeking an accomplished AI/ML Technical Lead to drive the design, development, and deployment of advanced machine learning solutions that scale seamlessly in production environments. In this role, you’ll shape the strategy for how AI is leveraged across the organization, partnering with cross-functional teams to translate business goals into technical solutions that are not only state-of-the-art, but also ethical, secure, and reliable. This position is ideal for a hands-on leader who thrives at the intersection of research and engineering. You will mentor engineers and data scientists, establish best practices for MLOps, and ensure models deliver consistent value long after deployment. With opportunities to explore cutting-edge fields like generative AI, large language models, natural language processing, and computer vision, you’ll play a pivotal role in setting the technical standard for Octane’s AI initiatives while guiding the team toward innovation and measurable impact. Responsibilities: • Lead the end-to-end design, development, and deployment of advanced AI/ML systems, ensuring production environments are scalable, efficient, and highly performant., • Collaborate with cross-functional teams to define AI strategy, evaluate use cases, and translate business objectives into actionable technical solutions., • Build, optimize, and maintain machine learning pipelines, covering data ingestion, preprocessing, model training, evaluation, deployment, and ongoing monitoring., • Establish and champion MLOps best practices, including CI/CD for ML workflows, automated testing frameworks, and continuous model performance monitoring to prevent drift., • Serve as a technical mentor and leader, guiding engineers and data scientists on system architecture, coding standards, and efficient development practices., • Research and evaluate emerging AI methodologies, frameworks, and tools, integrating innovative approaches into the organization’s technology stack where applicable., • Ensure AI solutions meet ethical, security, and compliance standards, including model explainability, bias mitigation, and data privacy requirements., • Partner with engineering leadership to set technical strategy, establish architectural guidelines, and define standards that shape the future of AI initiatives at Octane. Requirements: • Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field with 5+ years of professional experience, or Bachelor’s degree with 8+ years of experience in AI/ML engineering., • Proven expertise with leading ML/DL frameworks such as TensorFlow, PyTorch, or JAX, with hands-on experience training and deploying models., • Strong programming proficiency in Python, with additional experience using languages such as C++ or Java for performance-critical applications., • Practical experience with MLOps tools and workflows, including MLflow, Kubeflow, SageMaker, or Vertex AI to streamline model lifecycle management., • Deep understanding of data engineering concepts such as data pipelines, preprocessing, and distributed computing, as well as hands-on experience with cloud platforms (AWS, Azure, or GCP)., • Demonstrated success designing, deploying, and optimizing AI/ML systems at scale, including model serving, monitoring, and iteration., • Strong communication and collaboration skills, with the ability to influence technical direction and align diverse stakeholders. Preferred Skills: • Experience with generative AI and large language models (LLMs), including prompt engineering and fine-tuning approaches., • Knowledge of advanced ML domains such as natural language processing (NLP), computer vision, reinforcement learning, or recommendation systems., • Familiarity with containerization and orchestration technologies, including Docker and Kubernetes, to support scalable deployment., • Hands-on experience with infrastructure-as-code (IaC) tools, such as Terraform or Ansible, to enable automated and reproducible infrastructure management., • Contributions to the AI/ML community, such as open-source projects, conference presentations, or peer-reviewed research publications. Compensation: In addition to salary, Total Rewards include bonus eligibility, a stock option package, and benefits as outlined below. The role described above offers a base salary of $150,000 to $210,000 + bonus incentive eligibility. Your offer will be based on location, the alignment of your qualifications with the requirements of the job and internal equity. Benefits: • Robust Health Care Plans (Medical, Dental & Vision), • Generous Parental Leave, • Flexible Time Off (FTO) Policy - Time Off When You Need It, • Retirement Plan (401k) with company match!, • Educational Assistance/Tuition Reimbursement up to $3K/year, • Life Insurance (Basic, Voluntary & AD&D), • Short Term / Long Term Disability, • Robust Ancillary benefits including accident insurance, hospital insurance, etc, • Wellhub (Gympass) Wellness Benefit, • Powersports Safety Benefit Disclaimer: The above statements are intended to describe the general nature and level of work being performed by associates assigned to this classification. They are not to be construed as an exhaustive list of all responsibilities, duties, and skills required of personnel so classified. All personnel may be required to perform duties outside of their normal responsibilities from time to time, as needed. Octane Lending is an equal opportunity employer committed to providing equal employment opportunity without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other protected status with respect to recruitment, hiring, promotion and other terms and conditions of employment. #LI-MZ1 #LI-Hybrid

The Data Scientist will work closely with the Product, Data, and Research teams to analyze labor market trends, workforce dynamics, and economic patterns. The role involves cleaning, organizing, and interpreting large-scale datasets to develop innovative models, datasets, and visualizations that provide actionable insights into the future of work. The ideal candidate will demonstrate strong statistical thinking, a solid grasp of machine learning principles, and the ability to apply core methodologies such as predictive modeling, econometric analysis, and time series forecasting. This position requires a collaborative mindset to work cross-functionally, ensuring the seamless integration of analytical insights into Lightcast's products and services. • Use SQL, Python, or other analytical tools to query, clean, and analyze large datasets., • Analyze labor market trends across dimensions such as workforce composition, job demand, employment patterns, and wage dynamics., • Apply advanced techniques including time series forecasting, clustering, regression analysis, and machine learning algorithms (e.g., decision trees, random forests, gradient boosting, support vector machines, k-means clustering) to identify patterns and forecast labor trends., • Build and maintain scalable data and model pipelines using orchestration tools like Apache Airflow, Luigi, or Sagemaker Pipelines, and model tracking tools such as MLflow., • Collaborate cross-functionally to define problem statements, gather and analyze data, integrate models into products, and translate insights into actionable recommendations for technical and non-technical audiences., • Stay informed on advancements in labor market analytics, statistical modeling, and machine learning technologies., • Bachelor’s or Master’s degree in Data Science, Statistics, Economics, Computer Science, or a related quantitative field., • 2+ years of industry experience or academic research applying statistical or machine learning approaches to real-world data problems., • 2+ years of experience in labor market analytics, workforce intelligence, or related domains (preferred)., • Proficiency in Python, SQL, and machine learning libraries such as Scikit-learn or PyTorch., • Demonstrated ability to write clean, scalable code and independently prototype data solutions., • Solid understanding of machine learning techniques such as classification, regression, and time-series forecasting., • Experience with cloud platforms (e.g., AWS) and orchestration tools like Apache Airflow for managing large datasets and workflows., • Strong statistical reasoning and ability to translate complex data into strategic business insights., • Excellent interpersonal, written, and verbal communication skills, with the ability to convey technical topics to diverse audiences., • Experience working with large labor market datasets (e.g., government labor statistics, survey data, or job market intelligence platforms) (preferred)., • Proficiency with data visualization tools such as Tableau, Power BI, or Plotly (preferred).

About the Job: LaunchDarkly’s AI Specialist will be at the forefront of revolutionizing how AI engineers think about, release, monitor, and optimize their agents, scaling up our LaunchDarkly for AI from initial market validation to an industry-leading product. You will represent deep, specialized LD4AI product knowledge, sharing your expertise with prospects and customers, gathering critical feedback that shapes product development, and driving early-stage adoption. Your expertise will be instrumental in establishing the Solutions Engineering frameworks that will guide our future success. This is a role for builders and storytellers who thrive in undefined spaces. You will be expected to build – meaning the construction of integrations, technical content, whitepapers, and tutorials, all alongside attractive demos of our product customized to strategic engagements. You'll work with the innovation coming out of LaunchDarkly's Product team and make a significant impact on how companies build and deploy AI applications. Responsibilities: Expert-Level Solutions/Sales Engineering • Represent the trustworthiness and confidence of serious expertise in practical AI applications in customer conversations (especially as an escalation point above an SE SME), • Spearhead the early-stage implementation and adoption of LD4AI at scale, working closely with existing customers to ensure activation and churn prevention (alongside feedback), • Develop and document Solutions Engineering playbooks and best practices that scale beyond our first customers, • Function as a tremendous partner to the LD4AI Chief of Staff, surfacing revenue-related insights with respect to the maturation of the product accordingly, • Support LD4AI POVs ran by on-the-ground SEs Collect and Propagate Product Feedback • Collaborate extensively with product and engineering teams to ensure product concepts are technically feasible and align with LaunchDarkly's strategic goals, • Drive continuous improvement by monitoring product performance, user experience, and market response, iterating based on actionable data and insights, • Confirm that LD4AI’s roadmap adheres to market demand and deliver exceptional user experiences, especially for the AI developer persona – vocalizing objections with data Build LD4AI Into The World • Deliver integrations against common, quantified customer requests in the form of code contributions, architecture diagrams, and whitepapers, • Function as a key technical asset in (with the Head of AI and the partnership team) technical partnerships with advantageous potential partners (like Anthropic, DataBricks, etc…), • Publicly evangelize LD4AI at mainstream industry conferences, webinars, partner engagements, and strategic meetings Technical Leadership & Communication • Function as the primary owner of the disbursement of enablement material to the SE team, particularly to the designated by team/region SE LD4AI SMEs (for which you have partial, dotted-line accountability), • Co-own Revenue Enablement of LD4AI along with the Head of AI and the LD4AI tetrad, • Work with the AI Researcher, the PMM team, and the Head of AI to build and maintain competitor playbooks Qualifications: AI & Technical Expertise • This role requires a minimum of 12 years of related technical experience, • Extensive experience with AI applications—building, implementing, or selling AI solutions at scale, • Experience building multi-agent systems using frameworks like LangGraph, AgentBuilder, or AgentCore, • Hands-on experience evaluating AI agent performance at scale using automated evaluation methods, • Deep understanding of LLM mechanics (you've read 'Attention is All You Need' and can explain transformer architecture in detail), • Experience building or interfacing with MCP (Model Context Protocol) servers, • Strong Python skills with experience building in PyTorch or TensorFlow, • Strong foundation in software engineering principles and current market trends Mindset & Approach • Strong but loosely-held opinions about AI—you have a point of view but update it based on evidence, • Ability to anticipate where the AI landscape is heading and position products accordingly, • Deep curiosity about how AI changes software development, with an obsession for staying current on new AI technology, • Natural storyteller who can take new technology and craft compelling narratives that resonate with technical audiences, • Thrive in ambiguity—you love figuring it out, building new processes, and working in undefined spaces Pay: Target pay ranges based on Geographic Zones* for Level 5: • Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $191,000 - $263,000**, • Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $172,000 - $237,000**, • Zone 3: All other US locations - $163,000 - $224,000** LaunchDarkly operates from a place of high trust and transparency; we are happy to state the pay range for our open roles to best align with your needs. Exact compensation may vary based on skills, experience, and location. *Within the United States, our geographic pay zones are defined by counties surrounding major metropolitan areas. **Restricted Stock Units (RSUs), health, vision, and dental insurance, and mental health benefits in addition to salary. About LaunchDarkly: Modern software delivery was supposed to be the foundation for a thriving digital business but reality has proven otherwise. Slow, inefficient development cycles, costly outages, and fragmented customer experiences are preventing developers from building their best software. The LaunchDarkly platform helps developers innovate on new features faster while protecting them with a safety valve to instantly rewind when things go wrong. Developers can target product experiences to any customer segment and maximize the business impact of every feature. And by gradually rolling out new application components, they escape nightmare "big-bang" technology migrations. The LaunchDarkly platform was built to guide engineers to the next frontier of DevOps by: • Improving the velocity and stability of software releases, without the fear of end customer outages, • Delivering targeted experiences by easily personalizing features to customer cohorts, • Maximizing the business impact of every feature through the ability to experiment and optimize, • Coordinating the release and optimization of software to provide consistent experiences across mobile platforms and device types, • Improving the effectiveness and productivity of engineering teams, by providing insights into engineering cadence and stability At LaunchDarkly, we believe in the power of teams. We're building a team that is humble, open, collaborative, respectful and kind. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status. LD invites any applicant to review our written Affirmative Action Plan. To do so, contact People Ops at ___. Do you need a disability accommodation? Fill out this ___ and someone from our People Operations team will contact you for assistance.

Sr. Engineering Manager, AI/ML Serving Platform The AI/ML Serving Platform team provides foundational tools and infrastructure used by hundreds of AI/ML engineers across Pinterest, including recommendations, ads, visual search, growth/notifications, trust and safety. We aim to ensure that AI/ML systems are efficient, healthy (production-grade quality) and fast (for modelers to iterate upon). Pinterest is seeking a Sr. Engineering Manager to lead the team that builds the serving and deployment infrastructure for all AI/ML models at Pinterest. Systems include: • Ultra-high-performance C++ model inference engine for production recommendations and content ranking systems. TorchScript + CUDA Graph models on GPU inference, serving 500+M inferences/second., • Production GenAI & LLM model inference stack for emerging use cases., • Model routing, deployment, monitoring. Kubernetes-based provisioning., • Feature fetching, caching, and logging What you’ll do • Lead the team to deliver continual improvements in advanced model architectures, cost-efficient resource utilization, and AI/ML developer productivity., • Set technical direction for the team based on company and org priorities, • Coach and develop talent on the team. What we’re looking for: • Experience managing platform engineering teams with many cross-organizational customers, • Experience leading the development of large-scale distributed serving systems, • Experience with AI/ML inference technologies (e.g. PyTorch, TensorFlow) for online serving at Web scale, • Bachelor’s degree in Computer Science, a related field or equivalent experience. In-Office Requirement Statement: • We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection., • This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country. Relocation Statement: • This position is not eligible for relocation assistance. Visit our___ page to learn more about our working model. #LI-REMOTE #LI-AH2

Who are we? Smarsh empowers its customers to manage risk and unleash intelligence in their digital communications. Our growing community of over 6500 organizations in regulated industries counts on Smarsh every day to help them spot compliance, legal or reputational risks in 80+ communication channels before those risks become regulatory fines or headlines. Relentless innovation has fueled our journey to consistent leadership recognition from analysts like Gartner and Forrester, and our sustained, aggressive growth has landed Smarsh in the annual Inc. 5000 list of fastest-growing American companies since 2008. Summary As a Sr. Data Scientist at Smarsh, you will be analyzing a wide range of unstructured communications data to address problems for our customers through attentive listening, astute planning, and out of the box thinking to develop solutions and reporting results in an engaging manner. The role will involve working with other Senior Data Scientists and mentoring Associate Data Scientists in analyzing complex data, generating insights, and creating solutions as needed across a variety of tools and platforms. The ideal candidate for this position will possess the ability to perform both independent and team-based research and generate insights from large data sets with a hands-on/can do attitude of servicing/managing day to day data requests and analysis. This role offers a unique opportunity to get exposure to many problems and solutions associated with taking machine learning and analytics research to production. On any given day, you will have the opportunity to interface with business leaders, machine learning researchers, data engineers, platform engineers, data scientists and many more, enabling you to level up in true end-to-end data science proficiency. • Collect, analyze, and interpret small/large datasets to uncover meaningful insights to support the development of statistical methods / machine learning algorithms., • Development of machine learning models and other analytics following established workflows, while also looking for optimization and improvement opportunities, • Data annotation and quality review, • Exploratory data analysis and model fail state analysis, • Methodology, results and insights reporting, including model Governance report drafting in collaboration with senior team members, • Client/prospect guidance in machine learning model and analytic fine-tuning/development processes, • Providing guidance to junior team members on model development and EDA, • Working with Product Manager(s) to intake project/product requirements and translate these to technical tasks within the team’s tooling, technique and procedures, • Continued self-led personal development, • Bachelor’s degree in Computer Science, Applied Math, Statistics, or a scientific field, • 3-5 years’ experience working with data & analytics, • Experience working with Python, SQL and noSQL databases, • Experience with one or more data science and machine/deep learning frameworks and tooling, including scikit-learn, H2O, keras, pytorch, tensorflow, pandas, numpy, carot, tidyverse, • Command of data science and statistics principles (regression, Bayes, time series, clustering, P/R, AUROC, exploratory data analysis etc…), • Strong knowledge of key programming concepts (e.g. split-apply-combine, data structures, object-oriented programming), • Solid statistics knowledge (hypothesis testing, ANOVA, chi-square tests, etc…), • Knowledge of NLP transfer learning, including word embedding models (gloVe, fastText, word2vec) and transformer models (Bert, SBert, HuggingFace, and GPT-x etc.), • Experience with natural language processing toolkits like NLTK, spaCy, • Knowledge of microservices architecture and continuous delivery concepts in machine learning and related technologies such as helm, Docker and Kubernetes, • Knowledge of Agentic Processing, • Familiarity with training and evaluating transformer-based models, • Understanding and Experience of NLP Techniques in traditional pipelines, metrics, process and evaluation for supervised and unsupervised learning., • Familiarity with Deep Learning techniques for NLP., • Familiarity with LLMs; using ollama & Langchain, • Excellent verbal and written skills, • Proven collaborator, thriving on teamwork, • Preferred Qualifications, • Master’s or Doctor of Philosophy degree in Computer Science, Applied Math, Statistics, or a scientific field, • Familiarity with cloud computing platforms (AWS, GCS, Azure)

Job DescriptionJoin the Sleep Fitness Movement At Eight Sleep, we’re on a mission to fuel human potential through optimal sleep. As the world’s first sleep fitness company, we’re redefining what it means to be well-rested and building the most advanced hardware, software, and AI technology to make it possible. Our products power peak mental, physical, and emotional performance by transforming every night of sleep into a personalized, data-driven recovery experience. We are trusted by high performers, professional athletes, and health-conscious consumers in over 30 countries worldwide. Recognized as one of Fast Company's Most Innovative Companies in 2019, 2022, and 2023, and twice named to TIME's “Best Inventions of the Year.” We operate like a high-performance team: fast, focused, and motivated by impact. We don’t just ship; we iterate, refine, and obsess over the details that help our members sleep better and wake up stronger. Every role at Eight Sleep is a chance to create cutting-edge technology, collaborate with world-class talent, and help shape a future where sleep isn’t passive - it’s a powerful tool for living better. If you’re tired of the ordinary and driven to build at the edge of what’s possible, this is your moment. Join us and lead the movement that’s transforming how the world sleeps and what we’re all capable of when we wake up. High Standards. No Apologies. We operate with intensity because our mission demands it. At Eight Sleep, we bring the same mindset as the world’s top performers: focused, relentless, and always pushing to be in the top 1% of our craft. Think Kobe Bryant’s mamba mentality, applied to bold ideas, next-gen tech, and flawless execution. This isn’t a 9-to-5. Our team is deeply committed, often putting in 60+ hours a week –not because we’re told to, but because we’re invested. We’re here to build fast, push limits, and deliver without compromise. If you thrive under pressure and want to do the most meaningful work of your career, you’ll feel right at home. If you’re looking for something easier – this isn’t it. The Role Eight Sleep is looking for Machine Learning research interns to work on AI/ML problems in the sleep fitness and personal health space. You’ll work closely with a cross-functional team to scope problems, build end-to-end prototypes, validate with data, and iterate toward something we can ship. Along the way, you’ll receive hands-on mentorship, sharpen your technical toolkit, and present your results to leadership. Where appropriate, you may also develop your work into a publication. We’re seeking interns who care about outcomes, think in systems, and make data-driven decisions. If you’re excited to learn fast, collaborate deeply, and deliver meaningful improvements for users, we’d love to work with you. What You'll Help Build Example topics include: * Multimodal Activity Understanding: Build and fine-tune a vision- and physiology- foundation model that detects daily activities (workouts, meals, naps) from wearables, Pod signals, and phone context to explain sleep trends. * Next-Gen Time-Series Forecasting for Sleep: Push state of the art on multivariate forecasting to predict sleep stages, heart rate, HRV, and recovery days ahead - robust to missing data and lifestyle shifts. * Lifestyle-to-Sleep Simulation (“Digital Twin”): Create a high-fidelity simulator that models how choices (caffeine, exercise timing, alcohol, travel) ripple into tonight’s sleep and tomorrow’s readiness. * Adaptive Pod Thermoregulation: Learn personalized cooling/heating policies that react to micro-events (restlessness, awakenings) in real time - balancing comfort, sleep continuity, and energy. * Privacy-Preserving Personalization: Train better models without centralizing raw data: federated fine-tuning with differential privacy for sleep staging, anomaly detection, and forecasting. What You'll Need to Succeed * Minimum Qualifications * Working toward an undergraduate, graduate or doctoral degree in computer science, engineering, data science, applied mathematics, or equivalent. Doctoral degree paths are preferred for research focused internships. * Preferred Qualifications * It’s helpful if you meet one or more of the following qualifications, but it isn’t a requirement * Proficiency with an object-oriented programming language, such as Python, Swift, Objective C or Java * Experience with ML libraries, such as TensorFlow, PyTorch, CoreFlow, and Sklearn * Practical knowledge related to building and adapting algorithms for machine learning, time series analysis, multimodal sensing, foundation model fine-tuning, reinforcement learning and related areas * Familiarity with crafting, prototyping, and evaluating interactive systems * Excellent mathematical skills in linear algebra and statistics * Ability to collaborate with others * Problem solving skills * Applied ML Engineering internships: Experience with integrating research prototypes into production applications. Proficiency conducting ethnographic or other situated studies of human interaction with or through interactive technologies. Experience crafting, conducting, analyzing, and interpreting experiments and investigations * Demonstrated expertise with proven publication or track record in at least one of the areas: machine learning, statistics, econometrics, operations research, quantitative marketing, causal inference, time series analysis, stochastic modeling, optimization and decision theory * Research-Focused internships: Currently pursuing a doctoral degree. Research experience in Machine Learning and a demonstrable record of publishing academic research in peer-reviewed venues Why join Eight Sleep? Innovation in a culture of excellence Join us in a workplace where innovation isn’t just encouraged - it’s a standard. Our flagship product, the Pod, is a testament to our culture of excellence, beloved by hundreds of thousands of customers worldwide. At Eight Sleep, you will be part of a team that continuously pushes the boundaries of technology in sleep fitness. Immediate responsibility and accelerated career growth From your first day, you’ll take on substantial responsibilities that have a direct impact on our core business and product success. We are a small team that empowers you to own your projects and see the tangible effects of your efforts, enhancing both your professional growth and our company’s trajectory. Your path will be challenging but rewarding, perfect for those who thrive in fast-paced environments aiming for high standards. Collaboration with exceptional talent Work alongside other bright minds like you: at Eight Sleep exceptional intelligence and a passion for breakthroughs are the norms. Our team members are not only experts in their fields but also avid innovators who thrive in our dynamic, fast-paced environment. Equitable compensation and continuous equity investment We extend equity participation to every full-time team member, recognizing and rewarding your direct contributions to our success. This includes periodic equity refreshments based on performance, ensuring that as Eight Sleep grows and succeeds, so do you – perfectly aligning your achievements with the broader triumphs of the company. Your own Pod - and other great benefits Every Eight Sleep employee receives the very product that defines our mission: a Pod of their own. If you join us you’ll get your own Pod, along with: * Full access to health, vision, and dental insurance for you and your dependents * Supplemental life insurance * Flexible PTO * Commuter benefits to ease your daily commute * Paid parental leave At Eight Sleep we continually celebrate the diverse community different individuals cultivate. As an equal opportunity employer, we stay true to our values by ensuring everyone feels they can flourish and grow. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Job DescriptionWaabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech. With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: The Motion Planning team delivers the core module within the autonomy stack that makes decisions and generates trajectories for our self-driving trucks. As a research engineer for Learnable Planner you will support integration of new AI technologies into our autonomy/planner stack enabling our launch of fully driverless autonomous trucks. You will contribute towards Waabi's vision of a single AI system that learns end-to-end and in a provably safe manner as well as our revolutionary high-fidelity, closed-loop simulator, Waabi World. You will...- Integrate cutting-edge ML models in production planning stack from development to validation, deployment, and monitoring- Develop necessary interfaces and pipelines in simulation for testing prototype or production planning models- Work closely with motion planning sub-teams and research scientists to improve our planner architecture and develop rich and novel representations that can facilitate end-to-end solutions- Champion engineering excellence, ensuring high-quality, well structured and tested code.- Stay up-to-date with the latest advancements in the field of artificial intelligence, machine learning, computer vision, and self-driving technologies, and apply insights from the literature.- Work with large datasets from various sources as well as Waabi World, our high-fidelity simulator.- Contribute to the publication of research findings in conferences as well as Waabi's blog. Qualifications:- MS/PhD in machine learning, computer science, engineering, or a related field. Exceptional Bachelor’s students will also be considered.- Experience in ML-based or classical techniques for planning/decision making (e.g., imitation and reinforcement learning, optimization-based approaches, search methods, probabilistic reasoning).- Passion for taking research ideas and turning them into practical solutions for real-world applications.- Open-minded and collaborative team player with willingness to help others.- Solid understanding of computing fundamentals, including code efficiency.- Experience in deep learning frameworks such as PyTorch.- Proficiency in Python, Rust, C++ and/or CUDA. Bonus/nice to have:- Experience deploying ML/DL models to a production motion planning or related robotics stack.- Experience in iterating on a model including evaluation, introspection and fine-tuning.- Strong grasp of machine learning literature, including current trends and state-of-the-art techniques.- Comfortable with model compilation and exporting, lower level concepts like TensorRT, CUDA kernels.The US yearly salary range for this role is: $159,000 - $296,000 USD in addition to competitive perks & benefits. Waabi US Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus. Perks/Benefits:- Competitive compensation and equity awards.- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).- Unlimited Vacation.- Flexible hours and Work from Home support.- Daily drinks, snacks and catered meals (when in office).- Regularly scheduled team building activities and social events both on-site, off-site & virtually.- As we grow, this list continues to evolve! Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact! Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job DescriptionAbout Tahoe TherapeuticsTahoe Therapeutics is a biotechnology company pioneering a fundamentally new approach to drug discovery, one that begins with the biology of real patients. Our Mosaic platform is the first to make in vivo data generation scalable, with single-cell resolution, allowing us to map how drugs affect patient-derived cells in the body across a wide range of biological contexts. We are building the world’s largest in vivo single-cell perturbation atlas and using it to train multimodal foundation models that learn the context-dependent nature of gene function, disease progression, and drug response.By combining cutting-edge machine learning with the most biologically relevant datasets ever assembled in drug discovery, our mission is to find better drugs, faster and bring them to more patients who need them. Your roleWith Tahoe-100M, we solved one of the fundamental bottlenecks in building a virtual model of the cell: generating massive, perturbation-rich, single-cell datasets that capture real biological causality. With Tahoe-x1, we removed the second bottleneck: creating a modern platform for rapid iteration on model architectures and designs in a cost-efficient manner and at scale. At Tahoe, we embody a simple philosophy: build in the open, shoot for the moon, and we’re looking for people who want to push the frontier of what’s possible. As a Senior Machine Learning Scientist, you will play a leading role in designing the next generation of foundation models of gene regulatory networks powered by Tahoe’s large scale single-cell datasets such as Tahoe-100M and beyond. This role is well-suited for someone with a strong background in machine learning and statistics, and an interest in applying cutting-edge breakthroughs in ML to meaningful problems in drug discovery. We are looking for non-incremental thinkers with the skills to help build models that can make a real impact on drug discovery.Qualifications - Essential • PhD or equivalent practical experience in a technical field., • A proven track record of developing and applying deep learning methods, including experience with modern architectures such as transformers, state-space models, graph neural networks or diffusion-based generative models., • Proficiency with modern ML frameworks (e.g., PyTorch, JAX, or TensorFlow) and core scientific computing libraries (e.g., NumPy, SciPy, Pandas)., • A genuine enthusiasm for applying cutting-edge ML research to real-world biological problems and a bias towards action.Qualifications - Nice to have, • Prior experience with ML applied to problems in biology or chemistry., • Familiarity with multimodal modeling, contrastive learning or self-supervised learning., • Experience with large scale distributed ML techniques (e.g., FSDP, TP, dMoE, flash attention)Key Responsibilities, • Develop and apply machine learning techniques towards building multimodal foundation models that bridge the chemical and biological domains, i.e.: integrate models of chemical structure, target protein sequence and whole transcriptome scRNAseq., • Stay at the forefront of ML and computational biology research and rapidly adopt state-of-the-art techniques to our problems and datasets., • Collaborate with our team of biologists and engineers in cross-functional pods to test novel ML-driven hypotheses.Benefits, • Unlimited Paid Time Off (PTO)., • Monthly Lunch budget., • One-time Office set up budget.

Job DescriptionAbout Tahoe TherapeuticsTahoe Therapeutics is a biotechnology company pioneering a fundamentally new approach to drug discovery, one that begins with the biology of real patients. Our Mosaic platform is the first to make in vivo data generation scalable, with single-cell resolution, allowing us to map how drugs affect patient-derived cells in the body across a wide range of biological contexts. We are building the world’s largest in vivo single-cell perturbation atlas and using it to train multimodal foundation models that learn the context-dependent nature of gene function, disease progression, and drug response. By combining cutting-edge machine learning with the most biologically relevant datasets ever assembled in drug discovery, our mission is to find better drugs, faster and bring them to more patients who need them. Your roleWith Tahoe-100M, we solved one of the fundamental bottlenecks in building a virtual model of the cell: generating massive, perturbation-rich, single-cell datasets that capture real biological causality. With Tahoe-x1, we removed the second bottleneck: creating a modern platform for rapid iteration on model architectures and designs in a cost-efficient manner and at scale. At Tahoe, we embody a simple philosophy: build in the open, shoot for the moon, and we’re looking for people who want to push the frontier of what’s possible. As a Senior Machine Learning Engineer, you will play a leading role in designing the next generation of foundation models of gene regulatory networks powered by Tahoe’s large scale single-cell datasets such as Tahoe-100M and beyond. This role is well-suited for someone with a strong background in machine learning and statistics, and an interest in applying cutting-edge breakthroughs in ML to meaningful problems in drug discovery. We are looking for non-incremental thinkers with the skills to help build models that can make a real impact on drug discovery.Qualifications - Required • Solid Engineering and Computer Science fundamentals, ideally with a degree in CS, Math, or equivalent experience., • Exceptional engineering skills to iterate quickly on data processing and training pipelines, • Experience in building, testing, training, and deploying modern neural network architectures such as Transformers., • Experience with frameworks like PyTorch, Tensorflow, Keras, JAX and the ability to write hardware optimized code for distributed trainingQualifications - Desirable, • Experience with distributed deep learning using frameworks such as HF Accelerate, Deepspeed, Composer, TorchTitan, Megatron etc., • Experience with training large neural networks on multiple compute nodes.Key Responsibilities, • Stay at the forefront of ML and computational biology research and rapidly adopt state-of-the-art techniques to train AI virtual cell models on our massive single cell datasets., • Work together with ML Scientists to develop the next generation of compute optimized models like Tahoe-x1.Benefits, • Unlimited Paid Time Off (PTO)., • Monthly Lunch budget, • One-time Office set up budget

Job Description . Applied AI/ML Engineer San Francisco, New York, Kansas City, or Remote (US) Replica provides data about the built environment and ways people interact with it. With better data, human-context and an intuitive design, Replica helps public and private sectors make informed, effective, and responsive decisions. By showing how people live, move and work, we contextualize hard choices, allowing our clients to see around corners and understand the trade-offs surrounding their decisions. Whether for a city planner increasing public transit to underserved neighborhoods or for a grocery chain evaluating where to open a new location, Replica’s insights lets clients make more informed, people-centered decisions. We spun out of Alphabet in 2019 and recently secured series B funding from venture firms including Founders Fund, Innovation Endeavors, Sidewalk Labs, Firebrand Ventures, and Revolution’s Rise of the Rest Seed Fund. Today, we are a team of 34 employees with offices in San Francisco, New York, Kansas City and Remote. We value our customers, believe in being resourceful, and work in service of each other to scale our product. As we build our team, we are committed to pursuing and bringing together a diverse workforce and creating an environment of inclusion. We value our differences and we encourage all to apply. We are committed to equal opportunity regardless of race, color, ancestry, religion, gender, gender identity, parental or pregnancy status, national origin, sexual orientation, age, citizenship, marital status, disability, Veteran status, or any other status protected by the laws or regulations in the locations where we operate. The Role We’re looking for an Applied AI/ML Engineer to help design, implement, and scale advanced models that power Replica’s urban simulation and analytics products. This role is scoped at the Senior level or above: we expect candidates to operate at least at a Senior Engineer level, and for exceptional candidates, we are open to Staff or Principal-level. You’ll sit at the intersection of research and engineering, translating applied methods into production-ready models that deliver meaningful insights about mobility, land use, and activity patterns across the US. Unlike our infrastructure-oriented teams, your work will focus on algorithms, modeling, and applied AI/ML techniques that improve Replica’s products and unlock new capabilities for customers. Organizational Relationships Reports to: Director of Engineering Works closely with: Product and Data Science teams and other engineers on the Data Production team Collaborates with: Customer Success and Strategy teams to ensure models align with product needs and customer use cases Responsibilities • Design, prototype, and implement applied AI/ML models for mobility, activity, and behavioral modeling at scale., • Drive improvements to core models for routing, mode choice, demand estimation, and geospatial forecasting — balancing research innovation with production readiness., • Partner closely with Product and Data Science leadership to set technical direction for modeling initiatives, ensuring they align with customer and business needs., • Evaluate new data sources (e.g., vendor-provided mobility data, traffic sensors, geospatial layers) for quality, coverage, and fitness-for-use in Replica’s models., • Develop new algorithms to fuse Replica’s proprietary data with external sources (e.g., traffic sensors, land use, census, streaming data)., • Evaluate model performance, define success metrics, and iterate quickly to improve accuracy, robustness, and fairness., • Collaborate with data production engineers to transition prototypes into robust, production-quality systems used nationwide., • Contribute to modeling frameworks and shared libraries, mentoring peers and raising the technical bar across the team., • Stay current with advances in machine learning, optimization, and geospatial modeling, applying them pragmatically to Replica’s challenges. Minimum Qualifications, • Bachelor’s degree in Computer Science, Applied Mathematics, Engineering, or related field; advanced degree (MS/PhD) preferred., • 4+ years of professional experience in applied ML/AI, research engineering, or related roles., • Strong Python skills with experience in ML libraries (PyTorch, TensorFlow, scikit-learn) and numerical computing (numpy, pandas, scipy)., • Experience designing, training, and deploying AI/ML models in production., • Hands-on experience with large-scale data sets, especially geospatial or time-series data., • Familiarity with distributed computation frameworks (Dask, Spark, Ray) and cloud environments (GCP preferred)., • Proven ability to communicate technical decisions and tradeoffs clearly to both technical and non-technical stakeholders.What We Value, • We work in the service of others, • We understand that talent + diversity + curiosity + relentlessness wins, • We believe walking > talking, • We operate with thoughtful urgency, • We communicate openly and directly, • We build products people useBenefits, • Our people! We work as a team and are excited to contribute to city planning, • Competitive salary based on experience and potential for impact, • Equity at an early stage startup, • Health benefits including medical, dental, vision, and FSA options, • 401k account + employer safe harbor contribution, • Offices in San Francisco, CA, New York and Kansas City, • Replica is committed to fair and equitable compensation practices., • The base salary range for this position is $157,500 to $239,800. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to relevant qualifications, depth of experience, skill set, certifications, training, education, and specific work location. The compensation packages may be adjusted based on the candidate’s work location, due to differences in the cost of living for the given location. Our position titles may also span multiple career levels., • Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions., • To perform this job successfully, an individual must be able to perform each essential function satisfactorily., • The requirements listed are representative of the knowledge, skill and/or ability required., • Ability to operate at both a strategic/conceptual level and at a detailed, operational level metrics driven; highly disciplined, • Must have strong interpersonal skills, maturity and good judgment and be capable of communicating with a diverse range of individuals, • A hands-on, action-oriented approach that fits well with the entrepreneurial, fast-paced culture, • Engaging leadership style that builds and sustains credibility with colleagues, clients and other stakeholders Powered by JazzHR OmyiLKdP3z

Job DescriptionAbout Workato Workato transforms technology complexity into business opportunity. As the leader in enterprise orchestration, Workato helps businesses globally streamline operations by connecting data, processes, applications, and experiences. Its AI-powered platform enables teams to navigate complex workflows in real-time, driving efficiency and agility. Trusted by a community of 400,000 global customers, Workato empowers organizations of every size to unlock new value and lead in today's fast-changing world. Learn how Workato helps businesses of all sizes achieve more at workato.com. Why join us? Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company. But, we also believe in balancing productivity with self-care. That's why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives. If this sounds right up your alley, please submit an application. We look forward to getting to know you! Also, feel free to check out why: * Business Insider named us an "enterprise startup to bet your career on" * Forbes' Cloud 100 recognized us as one of the top 100 private cloud companies in the world * Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America * Quartz ranked us the #1 best company for remote workers Responsibilities We are looking for an exceptional AI Research Scientist to join our growing team. In this role, you will be responsible to: * Explore workflow‑aware planning, cost‑optimised RAG, tool‑use evaluation, and multi‑agent collaboration. * Prototype and benchmark models; present findings internally and externally. * Collaborate with Product & Engineering to ship research‑backed features. * Contribute to open‑source repos and author technical blogs. Requirements Qualifications / Experience / Technical Skills * MS/PhD in Computer Science, ML, or related field—or equivalent experience. * Hands‑on with PyTorch/JAX and modern LLM frameworks. * Strong publication record in top-tier ML venues (NeurIPS, ICML, ICLR) or demonstrable impactful experimental work; hands‑on experience with large‑scale model training, transformer architectures, reinforcement‑learning techniques, and CUDA. Soft Skills / Personal Characteristics * Curiosity‑driven and self‑directed. * Ability to explain complex ideas to non‑experts. * Team player who welcomes feedback and knowledge‑sharing. (REQ ID: 2124)

Job Description At Philo, we're a group of technology and product people who set out to build the future of television, marrying the best in modern technology with the most compelling medium ever invented — in short, we're building the TV experience that we've always wanted for ourselves. In practice this means leveraging cloud delivery, modern tech stacks, machine learning, and hand-crafted native app experiences on all of our platforms. We aim to deliver a rock solid experience on the streaming basics, while cooking up next generation multi-screen and multi-user playback experiences. Senior Machine Learning Engineer (Recommendation Systems) Philo's recommendation system improves user engagement and customer satisfaction by tailoring content discovery to individual preferences and viewing habits. We want users to be confident that Philo will have something they want to watch every time they open the app. We are seeking a Senior Machine Learning Engineer to lead our content personalization efforts, shaping experiences that impact millions of users. In this role, you will research, design, and build advanced algorithms and large-scale systems that power Philo's recommendation engine. As a senior member of a growing team, you will tackle complex machine learning challenges and collaborate with data science, product, infrastructure, and backend engineering teams to deliver innovative, data-driven personalization solutions. Your work will directly impact content discovery, deepen user engagement, and drive long-term retention. Responsibilities: • Lead development of recommendation systems: Design, build, and optimize advanced algorithms for SVOD, Live TV, and FAST personalization., • Drive ML innovation at scale: Conduct deep dives into models and system components, ensuring performance, scalability, and robustness across regions and product areas., • Own the ML pipeline: Build and maintain reliable pipelines for data extraction, feature engineering, model training, testing, and deployment., • Collaborate with Product, Data Science & Engineering: Translate product requirements into ML solutions, set clear expectations, and deliver measurable improvements in user engagement., • Advance deep learning in recommendations: Apply frameworks such as TensorFlow, PyTorch, or similar to develop state-of-the-art recommendation models., • Experimentation: Conduct rigorous A/B testing and ML experiments to understand model performance and iterate rapidly based on feedback., • ML Vision and Roadmap: Contribute to the strategic planning of the recommendations roadmap, aligning engineering efforts with business objectives and user needs., • 8+ years of experience in backend engineering and/or data science, including 4+ years focused on machine learning. Experience with recommendation systems is a big plus., • Strong coding skills in Python, as well as proficiency in using ML frameworks like PyTorch or TensorFlow., • Excellent analytical and problem-solving skills, with the ability to translate complex technical challenges into business solutions., • Proven track record of leading projects and delivering impactful machine learning solutions., • Strong communication and documentation skills; capable of explaining complex, technical concepts to non-technical stakeholders and to diligently document your work to help the team as a whole learn and move quickly. At Philo, we're a company that puts people first—both our subscribers and our team. We empower our colleagues to do their best work while supporting one another in pursuing shared goals. We value pragmatism, pride in our work, and passion, with transparency and openness as fundamental parts of our culture. We're committed to diversity, equity, inclusion, and accessibility as we grow the Philo team and shape the future of TV. We believe that a diverse range of voices and perspectives enables us to innovate faster and create the best experiences for our subscribers. Philo is proud to be an Equal Opportunity Employer. We're committed to supporting every candidate and employee. If you need an accommodation at any stage of the process, please email and we'll work with you to meet your needs. Philo offers 70+ top-rated networks, including AMC, BET, CMT, Comedy Central, Discovery Channel, Food Network, Hallmark Channel, HGTV, HISTORY, Investigation Discovery, Lifetime, MTV, Nickelodeon, OWN, VH1, We TV, and more. It also includes all the groundbreaking originals and blockbuster movies available with AMC+ and access to HBO Max Basic With Ads and discovery+. Our service also includes 100+ free channels and premium add-ons like STARZ and MGM+. Our extensive library boasts over 85,000 titles, and our unlimited DVR allows users to save their favorite shows and movies for up to a year, skipping ads for a seamless viewing experience. Stream on up to three devices simultaneously, whether on your phone, tablet, laptop, or TV using Roku, Apple TV, Fire TV, Samsung TV, Android TV, Vizio TV, or Chromecast. Philo is headquartered in San Francisco, with offices in New York City and Cambridge, MA. Our leadership team includes alums from HBO, Tubi, and Meraki, and is backed by NEA and industry partners like Warner Brothers Discovery, Viacom, AMC, and A&E. Join us at Philo and be part of a team that's shaping the future of TV! Status: Full-time Location: San Francisco, CA or remote within the U.S. Compensation: Includes annual salary, company stock options, and health benefits. Salary is determined by experience and location: • San Francisco, New York City: $175K - $235K, • Boston, DC Metro, Los Angeles, Seattle: $165K - $225K, • Denver, Atlanta, Austin, Las Vegas, Sacramento, Chicago: $155K - $215K, • Full health, dental and vision coverage for you and your family, • 401(k) plan with employer contributions (we match 100% of deferrals up to 3% of pay and 50% of the next 2% of pay), • Flexible working hours, • Up to 20 weeks of fully paid parental leave, • Unlimited paid time off for vacation and sick leave, • $2,000 annual vacation bonus (we pay you to take a two week vacation), • $5,250 annually for professional development and educational assistance, • $1,250 annual home office + TV stipend during first year of employment ($250 annually thereafter), • $500/month ($6,000/year) bonus for employees who commit to working at least 3 days per week in our offices, plus generous commuter benefits ($315/month towards transit, rideshare, bike rental, or parking at our HQ office in San Francisco), • Free Gympass subscription — an all-in-one corporate benefit that gives employees the largest selection of gyms, studios, classes, training and wellness apps, • Dog-friendly office Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Job DescriptionWaabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech. With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: The Motion Planning team delivers the core module within the autonomy stack that makes decisions and generates trajectories for our self-driving trucks. As a research scientist working on Learnable Planner, you will invent new AI technologies that support scalable planning solutions enabling our launch of fully driverless autonomous trucks. You will contribute towards Waabi's vision of a single AI system that learns end-to-end and in a provably safe manner as well as our revolutionary high-fidelity, closed-loop simulator, Waabi World. You will...- Design and execute on a research agenda for deep-learning based motion planning for self-driving.- Leverage and advance the state-of-the-art in robotics and machine learning to enable safe self-driving at scale, with advanced techniques in imitation and reinforcement learning, planning and search, perception and prediction, simulation, foundation models and more.- Support deploying solutions to our production systems, collaborating closely with platform teams to ensure seamless integration of research findings into production systems.- Stay up-to-date and advance beyond the state-of-the-art in artificial intelligence, machine learning, computer vision, and self-driving technologies.- Champion engineering excellence, ensuring high-quality, well structured and tested code.- Submit and publish work externally at top machine learning, computer vision, and robotics conferences (NeurIPS, ICLR, ICML, CVPR, etc.) and post to our company blog. Qualifications:- MS/PhD degree in Computer Science, AI, Machine Learning, Computer Vision, Robotics and/or similar technical field(s) of study. Exceptional Bachelor’s students will also be considered.- Experience in planning/decision making approaches (e.g., imitation learning, reinforcement learning, optimal control, optimization based approaches, search methods, probabilistic decision making).- Demonstrated research experience through previous internships, work experience, research projects, and papers at top conferences.- Strong quantitative background and coursework in or working knowledge of linear algebra, calculus, and probability.- Proficient in reading and coding in Python.- Passionate about self-driving technologies, solving hard problems, and creating innovative solutions. Bonus/nice to have:- Previous experience in self-driving technology. - Experience deploying ML/DL models to a production motion planning or related robotics stack.- Proficiency in Pytorch, Rust, C++ and/or CUDA.The US yearly salary range for this role is: $158,000 - $269,000 USD in addition to competitive perks & benefits. Waabi US Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus. Perks/Benefits:- Competitive compensation and equity awards.- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).- Unlimited Vacation.- Flexible hours and Work from Home support.- Daily drinks, snacks and catered meals (when in office).- Regularly scheduled team building activities and social events both on-site, off-site & virtually.- As we grow, this list continues to evolve! Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact! Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job Description Our mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. At our firm, we believe the most impactful safety research will require access to frontier AI systems. The most powerful AIs will operate not just on text but also other modes of data, including images, video and audio. Such models have potential to augment human creativity and productivity in exciting ways. However, we are very concerned about the risks introduced by powerful multimodal AIs. The Multimodal team builds and studies multimodal models to better understand and mitigate these risks. Our team works across many parts of a large stack that includes training, inference, system design and data collection. Some of our core focus areas are: Foundational Research We develop new architectures for modeling multimodal data and study how they interact with text-only models at scale. Building Infrastructure We work on many infrastructure projects including: • Complex multimodal reinforcement learning environments., • High-performance RPC servers for processing image inputs., • Sandboxing infrastructure for securely collecting data. Data Ingestion We are more interested in running simple experiments at large scale than smaller complex experiments. This requires access to very large sources of multimodal data. We develop tooling to collect, process and clean multimodal data at scale. Because we focus on so many areas, the team is looking to work with both experienced engineers and strong researchers, and encourage anyone along the researcher/engineer curve to apply. You may be a good fit if you: • Have significant software engineering experience, • Are results-oriented, with a bias towards flexibility and impact, • Pick up slack, even if it goes outside your job description, • Enjoy pair programming (we love to pair!), • Want to learn more about machine learning research, • Care about the societal impacts of your work Strong candidates may also have experience with: • High performance, large-scale ML systems, • GPUs, Kubernetes, PyTorch, or OS internals, • Language modeling with transformers, • Reinforcement learning, • Large-scale ETL The expected salary range for this position is: Annual Salary: $230,000—$400,000 USD Logistics Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Compensation and Benefits* Our compensation package consists of three elements: salary, equity, and benefits. We are committed to pay fairness and aim for these three elements collectively to be highly competitive with market rates. Equity - For eligible roles, equity will be a major component of the total compensation. We aim to offer higher-than-average equity compensation for a company of our size, and communicate equity amounts at the time of offer issuance. US Benefits - The following benefits are for our US-based employees: • Optional equity donation matching., • Comprehensive health, dental, and vision insurance for you and all your dependents., • 401(k) plan with 4% matching., • 22 weeks of paid parental leave., • Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more!, • Stipends for education, home office improvements, commuting, and wellness., • Fertility benefits via Carrot., • Daily lunches and snacks in our office., • Relocation support for those moving to the Bay Area., • This compensation and benefits information is based on our good faith estimate for this position as of the date of publication and may be modified in the future. Employees based outside of the US will receive a different benefits package. The level of pay within the range will depend on a variety of job-related factors, including where you place on our internal performance ladders, which is based on factors including past work experience, relevant education, and performance on our interviews or in a work trial. How we're different We believe that the highest-impact AI research will be big science. At our firm, we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to joining our firm, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! We are a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

Job DescriptionCoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at . What You'll Do The Field Engineering team at Weights & Biases plays a vital role in ensuring customer success and adoption of our platform. As part of this team, we partner with Sales, Support, Product, and Engineering to lead technical success after the sales process. We work closely with some of the most advanced AI teams in the world, helping them build, optimize, and scale their ML and GenAI workflows across industries such as computer vision, robotics, natural language processing, and large language models (LLMs). About the Role We're hiring a Post-Sales AI Solutions Engineer (AISE), Scale Customer Success to help customers successfully implement and scale AI/ML workflows and GenAI/agentic applications on Weights & Biases. You will design and deliver technical enablement and adoption programs that reach many customers at once, create reusable assets that improve self-serve success, and use product signals and feedback loops to continuously improve outcomes. Key Responsibilities • 3–5 years of relevant experience in a similar role, • Strong programming proficiency in Python, • Experience with deep learning frameworks (TensorFlow/Keras, PyTorch Lightning) and tools (e.g., Streamlit, LangChain), • Familiarity with cloud platforms (AWS, GCP, Azure), • Excellent communication and presentation skills, both written and verbal, • Experience with GenAI and LLMs, • Proficiency with HuggingFace, Fastai, scikit-learn, XGBoost, LightGBM, or Ray, • Experience with hyperparameter optimization solutions, • Background in data engineering, MLOps, or LLMOps, with tools such as Docker and Kubernetes, • You love collaborating with top AI teams to solve real-world ML and GenAI challenges, • You're curious about how to optimize AI workflows at scale, • Be Curious at Your Core, • Act Like an Owner, • Empower Employees, • Deliver Best-in-Class Client Experiences The base salary range for this role is $139,000 to $204,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we've posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs, including: • Medical, dental, and vision insurance - 100% paid for by CoreWeave, • Company-paid Life Insurance, • Voluntary supplemental life insurance, • Short and long-term disability insurance, • Flexible Spending Account, • Health Savings Account, • Tuition Reimbursement, • Ability to Participate in Employee Stock Purchase Program (ESPP), • Mental Wellness Benefits through Spring Health, • Family-Forming support provided by Carrot, • Paid Parental Leave, • Flexible, full-service childcare support with Kinside, • 401(k) with a generous employer match, • Flexible PTO, • Catered lunch each day in our office and data center locations, • A casual work environment While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration. California Consumer Privacy Act - California applicants only CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

Job Description Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster. We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI. We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services. If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe. About This Role: The Senior Director for the Model LifeCycle team will undertake a pivotal role in establishing both a dedicated team and a comprehensive managed platform to oversee the entire application development lifecycle, with a particular emphasis on utilizing Machine Learning models, including Large Language Models (LLMs). What You’ll Be Working On: * Building a Team of Machine Learning Experts and being the Site leader for the Model Life Cycle Team. * Manage fine-tuning systems for large foundation models (SFT, PEFT, LoRA, adapters), including multi-node orchestration, checkpointing, failure recovery, and cost-efficient scaling. * Implement and maintain end-to-end training pipelines for Large Language Models. * RFT and Reinforcement learning to the fine tuning and training sections * Distillation and reinforcement learning pipelines (e.g., preference optimization, policy optimization, reward modeling). * Dataset, model, and experiment management: versioning, lineage, evaluation, and reproducible fine-tuning at scale. What You’ll Bring to the Team: * Advanced degree in Computer Science, Engineering, or a related field. * 10+ years of industry experience leading and driving impactful projects in the AI Space * Lead and mentor a team of engineers with exceptional interpersonal skills, working autonomously while proactively collaborating with stakeholders at all levels. * Experience in Generative AI (Large Language Models, Multimodal). * Hands-on experience training, fine-tuning, and aligning LLMs using Reinforcement Learning and Reinforcement Fine-Tuning (RFT) techniques. * Proactive and collaborative approach with the ability to work autonomously * Passion for building cutting-edge AI products and solving challenging technical problems. Bonus Points: * PhD in Machine Learning, Computer Science, NLP, or a related field strongly preferred * Research publications at NeurIPS, ICML, ICLR, ACL, EMNLP, or impactful preprints in the LLM post-training space * Proficiency in Golang or Python for large-scale, production-level services and PyTorch * Contributions to open-source AI projects such as vLLM or similar frameworks. * Performance optimizations on GPU systems and inference frameworks. Benefits: * Competitive compensation * Restricted Stock Units * Paid time off & paid holidays * Comprehensive health, dental & vision insurance * Employer contributions to HSA account * Paid parental leave * Paid life insurance, short-term and long-term disability * Professional development & tuition reimbursement * Mental health & wellness support * Commuter benefits (parking & transit) * Cell phone stipend * 401(k) Retirement plan with company match up to 4% of salary * Volunteer time off Compensation Range Compensation will be paid in the range of up to $301,750 - $355,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicants knowledge, education, and abilities, as well as internal equity and alignment with market data. Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.

Job Description Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster. We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI. We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services. If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe. About This Role The Cloud Storage team at Crusoe is seeking a Staff Software Engineer to serve as a primary architect and visionary for our storage strategy. While a Staff Engineer leads features, a Senior Staff Engineer defines the multi-year technical roadmap that underpins our AI-scale infrastructure. You will be a multiplier, responsible for the architectural strategy, integrity and global scalability of our bespoke storage services. You will work at the physics of the stack, bridging the gap between high-performance NVMe hardware and globally distributed, S3-competitive object stores. What You’ll Be Working On * Architectural Vision & Strategy: Define and drive the long-term technical strategy for Crusoe’s storage engine. Identify industry trends (e.g., CXL, NVMe-oF) and integrate them into a cohesive roadmap. * System Programming Expertise: Leverage proven experience in system programming with languages such as C, C++, Go, and/or Rust to build the foundations of our V2 storage re-architecture. * Storage Protocols: Architect and implement solutions utilizing industry-standard storage protocols such as NFS, SMB, iSCSI, and NVMe/TCP. * Open Source Stewardship: Drive and maintain a track record of contributions to the open-source community (e.g., Ceph, GlusterFS, Lustre, Spectrum Scale, OpenEBS). * Technical Authority: Serve as the final arbiter for critical architecture decisions across the Foundations organization. Lead complex design reviews that intersect storage, networking, and virtualization. * Deep Performance Engineering: Lead "tiger teams" to solve the most ambiguous and difficult bottlenecks in the stack—from kernel-level IO context switching to global tail-latency in distributed clusters. * Strategic Collaboration: Work closely with Executive Leadership and Product to align technical capabilities with business milestones, such as our imminent path to IPO. What You’ll Bring to the Team * Cloud Storage Expertise: 12+ years of experience building and operating large-scale, complex distributed cloud computing infrastructure products. * Troubleshooting & Tuning: Strong troubleshooting and performance tuning skills; ability to profile and optimize the entire IO path. * High-Drive Mindset: Self-motivation to thrive in a fast-paced environment with a high degree of ownership and minimal supervision. * Masters of Consistency & Durability: Deep theoretical and practical knowledge of distributed state and data protection at petabyte scale. * Software Engineering Fundamentals: Mastery of professional software engineering practices for the full SDLC, including coding standards, build processes, and testing. * Communication & Collaboration: Ability to champion and lead initiatives across the engineering organization, such as tech talks and technical reading groups. Bonus Points * Public Cloud & AI/ML: Expertise in one or more Public Cloud offerings (AWS, GCP, Azure, OCI) and familiarity with AI/ML frameworks (PyTorch, Tensorflow, JAX) and MLOps. * High-Throughput I/O: Experience with cutting-edge I/O architectures like DAOS or SPDK. * Networking Foundations: Background in RDMA and high-performance networking, including SmartNICs and RoCEv2. * Distributed Systems Mastery: Experience with highly available and scalable systems such as Cassandra, MongoDB, Redis, or Kafka. * Theoretical Depth: Strong knowledge of distributed systems fundamentals including CAP Theorem, Paxos/RAFT, consistent hashing, and sharding strategies. * Education: Advanced degree (Master's or PhD) in Computer Science, Engineering, or a related field. Benefits: * Competitive compensation * Restricted Stock Units * Paid time off & paid holidays * Comprehensive health, dental & vision insurance * Employer contributions to HSA account * Paid parental leave * Paid life insurance, short-term and long-term disability * Professional development & tuition reimbursement * Mental health & wellness support * Commuter benefits (parking & transit) * Cell phone stipend * 401(k) Retirement plan with company match up to 4% of salary * Volunteer time off Compensation Range Compensation will be paid in the range of up to $240,000 - $310,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicants knowledge, education, and abilities, as well as internal equity and alignment with market data. Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.

Job DescriptionAbout Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do's, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We're looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we're creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! We are not able to provide visa sponsorship (including H-1B, OPT, or other employment-based visas) for this position. Candidates must be legally authorized to work in the United States without employer sponsorship now or in the future. About the Role Machine Learning is a cornerstone at Taskrabbit, and we're looking for a seasoned Senior Machine Learning Engineer to join our team and help shape the future of ML/AI at Taskrabbit. This is a unique, full-stack role for an individual who is passionate about the entire machine learning lifecycle—from initial research and model development to building the robust infrastructure required to deploy and scale your work. As a Senior Machine Learning Engineer, you will tackle exciting challenges that directly impact how people discover and connect with home services on the Taskrabbit platform. You will play a crucial role in advancing our capabilities in areas like search ranking, content discovery, and recommender systems. You will collaborate closely with data scientists and other engineers to design and implement novel algorithms, and you will partner with software engineers to ensure the scalability, reliability, and optimization of our models in production. What You'll Work On: • Model Development & Research: Research, design, and implement machine learning models to solve key business problems in areas like search ranking, recommendations, and content discovery., • End-to-End ML Lifecycle: Own the entire lifecycle of ML models, including feature engineering, training, evaluation, deployment, and monitoring., • Infrastructure & Scalability: Build scalable and reliable ML infrastructure and data pipelines that support reproducible feature engineering and machine learning model deployment in real-time, near real-time, and batch processes., • Performance & Quality: Build monitoring services to understand data quality and model performance of complex systems, and collaborate with engineering and science teams to optimize existing algorithms for training and evaluation., • BS, MS, or PhD in Computer Science, Statistics, Operations Research, or a related quantitative field., • 3+ years of industry experience building and deploying high-quality, production-grade machine learning models and systems., • Strong theoretical knowledge and hands-on experience in machine learning, particularly in areas like search, ranking, recommender systems, or NLP., • Solid software engineering skills with proficiency in one or more programming languages, including Python. The candidate should have experience with popular ML libraries like Scikit-learn, lightgbm, xgboost, TensorFlow, PyTorch, etc., • Proficiency in SQL is also required for writing complex queries and transforming data., • Experience building REST API-based services., • Experience with modern data and ML technologies, such as Docker, Kubernetes, Kafka, Airflow, data warehouses (eg snowflake, redshift or BigQuery), and data lakes., • Familiarity with dbt (Data Build Tool) is a plus for transforming and testing data., • Familiarity with tools for Infrastructure as Code, such as Terraform, and CI/CD pipelines., • Excellent communication skills, with the ability to present complex findings and recommendations clearly to both technical and non-technical audiences., • Taskrabbit is a Hybrid Company. We value flexibility and choice but also stay committed to regular in-person connection., • The People. You will be surrounded by some of the most talented, supportive, smart, and kind leaders and teams -- people you can be proud to work with!, • The Diverse Culture. We believe that we make better decisions when our workforce reflects the diversity of the communities in which we operate. Women make up half of our leadership team and our diversity representation is above that of the tech industry average. Taskrabbit is an equal opportunity employer and values diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, ancestry, citizenship, sex, gender, gender identity, sexual orientation, age, marital status, military/veteran status, or disability status. Taskrabbit is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Taskrabbit will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. Taskrabbit will never use text or chat applications to conduct interviews. We have a thoughtful and interactive interview process that includes an initial recruiter phone screen and several video-based interviews with our hiring teams. Communications will always be conducted by taskrabbit.com domain names.

Job Description Who we are: Formic is on a mission to reshape American manufacturing by making automation accessible to every factory. As labor constraints rise, costs increase, and global competition intensifies, automation is no longer optional for manufacturers that want to stay competitive. We deliver automation through a Robotics-as-a-Service model that combines industrial robotics, proprietary software, and full-service support into a single, integrated solution. By removing the traditional barriers of cost, complexity, and risk, we enable manufacturers to deploy automation quickly and realize measurable gains in throughput, safety, and operational efficiency without large upfront capital investment. Backed by leading investors including Lux Capital, Initialized Capital, Blackhorn Ventures, and Mitsubishi HC Capital North America, Formic is scaling rapidly and building the foundation for a new era of high-performance, Made in America production. About the team: The Software Engineering Team builds and operates the systems that power Formic's Robotics-as-a-Service platform. Engineering focuses on ensuring deployed systems are observable, resilient, and remotely diagnosable at scale. The team builds production-grade edge and cloud systems that support reliable data collection, remote troubleshooting, live video streaming, and continuous system improvement. This work directly impacts fleet uptime, service efficiency, and customer outcomes by ensuring Formic's monitoring and control infrastructure remains scalable, reliable, and continuously evolving. In this role you will: • Design and train learning-based manipulation systems for humanoid and mobile manipulation platforms, • Develop and maintain high-fidelity digital twins using Isaac Sim, MuJoCo, or similar tools, • Implement and evaluate approaches such as:, • Action Chunking with Transformers (ACT), • Diffusion Policies, • Behavior Cloning at Scale, • Vision-Language-Action (VLA) models, • Latent action or hierarchical skill models, • Work with modern foundation models for robotics (e.g., Pi0, Gemini ER 1.6 or similar), including adapting, fine-tuning, and deploying them for real-world tasks, • Contribute to development of a Universal Manipulation Interface (UMI) abstraction layer, • Build teleoperation-to-training data pipelines, • Design sim-to-real transfer strategies including domain randomization and system identification, • Evaluate policy robustness, generalization, and real-world performance, • Work closely with perception and controls teams to ensure stable closed-loop visuomotor policies, • Experience training embodied AI policies for real robots, • Familiarity with transformer-based action models (e.g., ACT), • Experience with diffusion policies or other generative control methods, • Experience working with or adapting large-scale models (e.g., Pi0, Gemini ER 1.6, or similar VLA / multimodal models), • Ability to deploy, fine-tune, and optimize models for real-world robotic systems (latency, robustness, reliability), • Strong understanding of sim-to-real challenges, • Experience working with multi-modal inputs (vision, proprioception, language), • Proficiency in Python and deep learning frameworks (PyTorch, JAX, etc.), • Experience integrating learned policies with real-time control systems, • Equity in Formic: Participate in our stock option program and share in the success of a fast-growing start-up backed by leading global investors, • Competitive & Uncapped Commission Structure: Designed to reward performance and impact in commission-eligible roles, • Comprehensive Healthcare Coverage: Medical, dental, and vision insurance through Blue Cross Blue Shield and Unum, with 99% of employee premiums covered and 75% coverage for dependents, with optional buy-up plans available, • Additional Insurance Benefits: FSA and DCFSA, life insurance, short-term disability, and long-term disability through Unum, all 100% employer-paid, • Employee Assistance Program (EAP): Fully funded by Formic, offering support when you need it most, • Paid Parental Leave Program: Up to 12 weeks of paid parental leave, • Company-sponsored 401(k): Invest in your future with our company-facilitated retirement savings plan, • Home Office Stipend: A one-time allowance for fully remote and hybrid employees to support an at-home or on-the-road work setup, • Monthly Cell Phone Reimbursement: Monthly stipend toward personal phone and internet expenses Final offers are customized based on experience, geographic location, market considerations, and a candidate's preferred balance of cash and equity. Our goal is to attract and reward top talent who will have significant impact, and we are open to thoughtful discussions to align on the right structure. Compensation Range:$145,000—$200,000 USD What we look for: We're building this company from the ground up, and every person we hire has an outsized impact on our culture, performance, and trajectory. While each team member brings unique strengths and perspectives, we look for people who align with our Operating Principles and embody them in action. If this sounds like you, Formic may be the right place for you! • Fearless Optimism: You make bold bets and default optimistic. You believe in the mission, aren't paralyzed by risk, and fear inaction more than failure. You see ambiguity as opportunity and bring energy to building what doesn't yet exist., • Create the Magic: You absorb complexity so customers don't have to. Whether your customer is external or internal, you focus on delivering experiences that are clear, fast, value-added, and outcome-driven. You don't say "not my job." You make things work., • Today, Not Tomorrow: You have a bias to action. You close the loop. You take extreme ownership. You understand that speed compounds, and you don't confuse activity with results., • Seek Truth: You think from first principles. You value data over ego and strong opinions loosely held. You're willing to challenge assumptions, including your own, in pursuit of the best answer., • Made of Rubber: You are resolute and adaptable. When things break or priorities shift, you rebound stronger. You treat setbacks as learning moments and move forward with grit. Formic is an equal opportunity employer. We do not discriminate on the basis of race, color, religion or religious creed, sexual orientation, gender, gender identity, marital status, family or parental status, disability, military or veteran status, or any other basis protected by law. All employment decisions are based on a person's merit, business needs, and role requirements. If you require further accommodations or have questions regarding accessibility of our roles, please reach out to . AI Use: At Formic, fairness and transparency are at the heart of our hiring process. We use AI-powered tools in some interviews to help our teams evaluate candidate responses, but all final hiring decisions are made by humans. You can learn more about how AI is used in our recruitment process by reviewing our AI Hiring Disclosure linked here.

Job DescriptionAbout us Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production. Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more. We're an ambitious team of 100+ working at the frontier of AI and have raised $60M in Series C funding from Wellington Management, CRV, Next47 and Y Combinator. The role We're building tools for the full Physical AI data stack — from data acquisition, through ingestion and curation at scale, to 3D rendering, annotation, and verification. You'll solve problems of large-scale efficient data transfer and storage, complex domain modelling, applying the latest machine learning models, and squeezing performance out of web browsers. You'll work with the biggest names in robotics and autonomous vehicles, and join a small, highly collaborative team at a crucial stage of accelerated development. You'll be a key driver of progress on a core part of our product, operating with a high degree of autonomy and crafting performant, reliable, and maintainable solutions at speed. What you'll do • Build and maintain high-performance frontend experiences, including rendering complex 3D scenes with thousands of objects at smooth frame rates, • Work across the full stack — from backend data pipelines and storage systems to frontend visualisation and interaction, • Take end-to-end ownership of projects, from product and architectural decisions through to deployment, monitoring, and measuring user impact, • Work with visual, spatial, and sensor data to make sense of the physical world, • Tackle complex domains at massive scale using simple, well-crafted solutions, • Take initiative, be proactive in problem-solving, and continuously seek improvementsWho we're looking for, • Experienced: you've seen a lot and built a lot — personally developed and maintained multiple systems from scratch, with a deep understanding of the trade-offs involved in building reliable, performant software at speed, • At home with challenging frontend work: you're comfortable rendering complex 3D scenes, working with spatial and sensor data, and optimising for browser performance, • Impact-driven: you want your work to have a tangible outcome for people and aren't satisfied by products that don't see the light of day, • A builder: you enjoy all aspects of building a complete product, are comfortable moving across the stack, and love problem-solving from first principles, • Comfortable with uncertainty: happy to tackle problems without a predefined solution, and excited to make decisions autonomously as you go, • A team player: you contribute your best work and actively help others do the same — you enjoy levelling up those around youExperience requirements, • Strong full-stack engineering experience, with a particular strength in complex, high-performance frontend work, • Experience with 3D rendering, WebGL, or similar technologies for visualising spatial/sensor data is a strong plus, • Proficiency in Python and/or TypeScript; experience with React a plus, • Familiarity with cloud infrastructure (GCP preferred) and containerised deployment (Kubernetes), • Backend: Python, • Frontend: TypeScript and React, • Deployment: Kubernetes, • Infrastructure: GCP, • Machine learning: PyTorch, CUDA, RayWhy Encord, • Competitive salary, commission, and meaningful equity in a high-growth startup, • Clear, accelerated growth opportunities as the company scales rapidly, • Strong in-person culture: 4–5 days/week in our newly launched North Beach loft office, • Flexible PTO to fully recharge, • 18 paid vacation days in the U.S. plus federal holidays, • Annual learning & development budget, • Comprehensive health, dental, and vision coverage, • Frequent travel opportunities across the U.S., London, and Europe

Job DescriptionWaabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech. With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: You will..- Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models.- Collaborate with data scientists and engineers to understand model requirements and optimize pipeline processes.- Automate the training, testing and deployment processes for machine learning models.- Continuously monitor and maintain model pipelines, ensuring optimal performance, accuracy and reliability.- Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness.- Ensure compliance with security and data privacy standards in all MLOps activities. Qualifications:- 3-5 years of experience in MLOps, DevOps or a related field.- Bachelor’s degree in Computer Science, Data Science or a related field.- Strong understanding of machine learning principles and model lifecycle management.- Proficiency in programming languages such as Python, with hands-on experience in machine learning frameworks like TensorFlow or PyTorch.- Experience with cloud platforms like AWS, Azure, or Google Cloud and their respective machine learning services.- Familiarity with containerization and orchestration tools such as Kubernetes and Docker.- Knowledge of CI/CD pipelines, automation tools and version control systems like Git.- Strong problem-solving skills and ability to troubleshoot complex issues.- Experience with monitoring tools and practices for model performance in production.- Ability to work collaboratively in cross-functional teams. Bonus/nice to have: - Experience with infrastructure-as-code (IaC) tools such as Terraform or Crossplane.- Knowledge of big data technologies like Apache Spark or Hadoop.- Familiarity with data engineering practices and tools.- Experience with A/B testing and model validation in production environments.- Relevant MLOps certifications (e.g., AWS Certified Machine Learning – Specialty, DataRobot MLOps Certification) are a plus.The US yearly salary range for this role is: $157,000 - $234,000 USD in addition to competitive perks & benefits. Waabi (US) Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus. Perks/Benefits:- Competitive compensation and equity awards.- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).- Unlimited Vacation.- Flexible hours and Work from Home support.- Daily drinks, snacks and catered meals (when in office).- Regularly scheduled team building activities and social events both on-site, off-site & virtually.- As we grow, this list continues to evolve! Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact! Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job DescriptionCompany Description About Sia Sia is a next-generation, global management consulting group. Founded in 1999, we were born digital. Today our strategy and management capabilities are augmented by data science, enhanced by creativity and driven by responsibility. We’re optimists for change and we help clients initiate, navigate and benefit from transformation. We believe optimism is a force multiplier, helping clients to mitigate downside and maximize opportunity. With expertise across a broad range of sectors and services, our 3,000 consultants serve clients worldwide from 48 locations in 19 countries. Our expertise delivers results. Our optimism transforms outcomes. Sia’s AI & Data Business Unit is the powerhouse of our firm’s innovation—merging cutting-edge Data Science, Generative AI, and advanced digital solutions to transform industries. With over 350 experts worldwide, we tackle projects from proof-of-concept to large-scale deployment, always pushing the boundaries of AI capabilities. Our 12 R&D labs in Europe and North America drive continuous research in areas like computer vision, MLOps, and deep learning, partnering closely with our business consultants for real-world impact. By joining Sia’s AI & Data team, you’ll step into a vibrant, collaborative environment that nurtures professional growth and empowers you to shape the future of AI-driven consulting. Job Description Join us as an experienced Generative AI Specialist designing and implementing cutting-edge GenAI/LLM solutions across diverse industries. You'll act as a vital bridge between technical teams (Data Science, ML, Platform) to deliver business-centric AI value. You'll guide clients on the optimal path—using techniques like RAG, agents, or fine-tuning—for cost-effective impact. Your responsibilities extend beyond prompting to architecting robust AI products via benchmarking, prototyping, and validation. You'll orchestrate the full AI workflow, ensuring seamless model integration optimized for performance, security, and scale, while tackling infrastructure challenges. We provide extensive training to support your success. If you're driven to push AI boundaries and help clients rapidly adopt GenAI with confidence, apply to make a real difference. Responsibilities: • LLM/GenAI System Development: Design, build, train, fine-tune, and deploy sophisticated AI models leveraging LLMs (e.g., GPT-x, Claude, Gemini, Llama, Mistral) and other generative techniques., • Assist in Solution Architecture: Support the GenAI Solution Architect in designing robust, scalable, and secure applications., • Application Development: Develop applications powered by GenAI models (both self-managed and API-accessible) that meet business needs and comply with applicable regulations (GDPR, EU AI Act, model licenses, etc.)., • Advanced Prompt Engineering: Design and optimize effective prompts (e.g., few-shot, Chain/Tree/Graph of Thought, ReAct, Self-reflection, guardrails), balancing simplicity and complexity to enhance analytical capabilities, refine outputs, improve user experience, and control interactions., • RAG Implementation: Design and implement Retrieval-Augmented Generation (RAG) architectures to improve accuracy and relevance by retrieving information from pre-determined knowledge sources, providing traceability (source attribution)., • Model Selection & Fine-Tuning: Select and fine-tune appropriate models (including multimodal - VLM, SLM - Visual Language Models, Small Language Models) to create higher-quality content (text, image, audio, code, etc.) and maximize business value creation opportunities., • Integration & Deployment (MLOps): Implement MLOps best practices for the GenAI lifecycle, including automated pipelines (CI/CD), versioning, monitoring, and maintenance in production environments (Cloud platforms like AWS, Azure, GCP). Ensure seamless integration into existing systems and with external tools/APIs, potentially utilizing standardized protocols (MCP)., • Evaluation & Responsible AI: Develop and execute rigorous evaluation frameworks to measure model performance, reliability, fairness, and safety. Ensure adherence to Responsible AI principles and help teams and clients navigate end-to-end security and compliance processes., • Research & Innovation: Stay abreast of the latest advancements in GenAI techniques, technologies, and frameworks. Experiment with new approaches and contribute to internal knowledge sharing., • Collaboration: Work effectively within cross-functional teams, communicating complex technical concepts clearly to diverse stakeholders (both technical and non-technical)., • Documentation: Document processes, methodologies, and best practices for knowledge sharing and future reference., • Use Case Differentiation: Distinguish between use cases suited for Generative AI versus traditional NLP applications (e.g., NER, sentiment analysis). Qualifications Education: • Master's degree or Engineering degree (or equivalent) in Computer Science, Engineering, Data Science, or a related quantitative field., • Strong programming skills, particularly in Python., • Proficiency in at least one major GenAI application framework (LangChain, LlamaIndex, etc.)., • Proven experience in NLP/NLU, vector embeddings, and semantic search., • Hands-on experience with fine-tuning LLMs., • Mastery of advanced prompting techniques (Chain/Tree/Graph of Thought, ReAct, etc.)., • Knowledge of both proprietary and open-source model ecosystems (OpenAI, Anthropic, Mistral AI, Hugging Face, models hosted on AWS/Azure/GCP, etc.)., • Experience with Cloud platforms (AWS, Azure, or GCP) and their associated MLOps/AI services., • Excellent communication skills (written and verbal), ability to explain complex technical concepts simply., • Strong analytical and complex problem-solving abilities., • Team player with the ability to collaborate effectively with diverse profiles., • Experience building agentic AI systems (e.g., LangGraph, AutoGen)., • Experience with vector databases (e.g., pgvector, Pinecone, Chroma, OpenSearch)., • Experience developing conversational AI systems / chatbots., • Familiarity with deep learning frameworks (PyTorch, TensorFlow)., • Understanding of or experience with protocols and standards for connecting LLMs to external tools and databases, such as Model Context Protocol (MCP)., • Experience deploying models at scale in production environments. Additional Information Compensation & Benefits • Base salary starting at $105,000, commensurate with experience and qualifications, • Annual Discretionary Bonus, • Healthcare coverage that includes 3 medical plan options: Anthem – EPO HSA, EPO HSA MERP, and PPO; dental and vision through MetLife; and life insurance policies through Mutual of Omaha, • Flexible Spending Account (FSA), • Paid Time Off, • Parental leave paid at 100% of base pay for all new parents, • 9 Company Holidays + 1 Floating Holiday, • 401(k) Plan - 4% matching and vested on day 1, • College save-up plan & college loan repayment plan, • Monthly cell phone stipend, • Pre-tax account for Parking and Mass Transit, • Sia provides several wellness and incentive programs free of charge through the firm medical plan – Anthem - such as:, • Gym Reimbursement, • LiveHealth Online, • Well-being Coach, • Building Healthy Families Program At Sia, we believe in fostering a diverse, equitable and inclusive culture where our employees and partners are valued and thrive in a sense of belonging. We are committed to recruiting and developing a diverse network of employees and investing in their growth by providing unique opportunities for professional and cultural immersion. Our commitment toward inclusion motivates dynamic collaboration with our clients, building trust by creating an inclusive environment of curiosity and learning which affects lasting impact. Please visit our website for more information. Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs. Office Workplace Guidelines Sia is committed to providing a flexible workplace environment that supports client, business, and market needs. Consultants located in our primary market office locations—New York City, Charlotte, Seattle, and San Francisco—are expected to live within a reasonable commuting distance and attend the office at least three days per week. For Consultants outside of our primary markets, we can offer more flexible in-person requirements in accordance with your location. Work Authorization & Sponsorship At this time, Sia does not intend to pursue employment with applicants who will require now or in the future visa by our company for work authorization in the United States (i.e., H1-B visa, F-1 visa (OPT), TN visa, or any other non-immigrant status). Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.

Job DescriptionSalary: $25 - $27/hr POSITION SUMMARY Position Title: Summer Intern, Bioinformatics and Data Science Reports to: Associate Director, Bioinformatics Status: Full-time, Non-Exempt, Summer Intern Duration: 10 12 Weeks (Summer 2026) Location: South San Francisco, CA (Hybrid or Remote) Summary: A summer internship opportunity is available for an undergraduate student interested in applying computational and artificial intelligence/machine learning (AI/ML) methods to biological and chemical data in a drug discovery setting. The intern will work closely with a cross-functional team spanning bioinformatics, machine learning, chemistry, and biology. This intern will be paired with a dedicated mentor to guide the student through this process and be a full member of the team throughout the internship. The intern will also have plenty of opportunities for networking and career development through conversations with people across multiple roles and teams at Assembly Bio. This role emphasizes hands-on experience with real datasets and exposure to modern computational pipelines used in early-stage therapeutic development. Specific responsibilities include, but are not limited to: • Analyzing biological and chemical datasets (e.g., RNA-seq, single-cell, proteomics or screening data) using Python or R, • Supporting development, testing and optimization of bioinformatics, cheminformatics and AI/ML pipelines, • Documenting workflows and results in a reproducible manner, • Presenting findings in internal meetings and contributing to reports Qualifications Include: • Pursuing a degree in Bioinformatics, Computational Biology, Data Science, Computer Science, or related field, • Strong programming skills in Python and/or R, • Some familiarity with common bioinformatics tools and libraries (e.g., Bioconductor, Scanpy,Seurat,PyTorch, TensorFlow), • Understanding of molecular biology concepts (e.g., gene expression, sequencing technologies), • Experience with statistical analysis and data visualization, • Ability to work independently and in a collaborative environment Preferred (Not Required) • Experience with single-cell data analysis, NGS pipelines, or cloud computing, • Exposure to machine learning or deep learningmethods in biological contexts, • Familiarity with version control (e.g., Git) What You Will Gain • Hands-on experience with real-world drug discovery datasets, • Exposure to interdisciplinary workflows bridging computation and biology, • Opportunity to contribute to impactful research in a fast-paced biotech environment How to Apply Please submit: • Resume/CV, • Brief statement of interest (12 paragraphs), • Optional: GitHub or project portfolio Pay Range: $25 - $27/hr The stated pay range for this position reflects the San Francisco Bay Area job market. Assembly Bio establishes pay ranges based on geographic work locations. Additional factors such as academic credentials and relevant experience will influence the actual salary offered. About Assembly Bio Assembly Bio (NASDAQ: ASMB) is an ambitious biopharmaceutical company with cutting-edge therapeutic clinical candidates capable of improving the lives of millions living with chronic hepatitis B virus (HBV) infection around the world, and research and preclinical programs focused on the discovery of novel antivirals to treat devastating viral diseases, including HBV, hepatitis delta virus (HDV) and herpesviruses. We pride ourselves on creating a culture and work environment that is scientifically driven, ambitious, and collaborative. We encourage diversity of thought that leads to great innovation and are looking to add great people to our dynamic team who are driven to transform the lives of patients. We set our sights highand pursue our goals with determination. Our unique organization stands ready to welcome talented, motivated individuals, who share our ambitions. As an equal opportunity employer, we are committed to diversity and inclusion and will not tolerate discrimination and harassment of any kind. All employment decisions are based on business needs, job requirements and individual qualifications, without regard to race, color, religion or belief, national, social or ethnic origin, sex (including pregnancy), age, physical, mental or sensory disability, HIV status, sexual orientation, gender identity and/or expression, marital, civil union or domestic partnership status, past or present military service, family medical history or genetic information, family or parental status, or any other status protected by the laws or regulations in the locations where we operate. Information for Recruitment Agencies Assembly Bio does not accept from recruiters/agencies any unsolicited resumes, or any candidate information including blinded resumes and will not be responsible for any fees related to resumes or candidate information that is unsolicited. Please do not contact hiring managers or Assembly Bio employees directly with any information related to a resume or a candidate. We handle all recruitment through our internal Human Resources team, and we will reach out to you directly should we wish to engage in a search. Your willingness to comply with this will significantly impact any decision we may make about doing business with you.