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Job DescriptionHinge is the dating app designed to be deleted In today's digital world, finding genuine relationships is tougher than ever. At Hinge, we’re on a mission to inspire intimate connection to create a less lonely world. We’re obsessed with understanding our users’ behaviors to help them find love, and our success is defined by one simple metric– setting up great dates. With millions of users across the globe, we’ve become the most trusted way to find a relationship, for all. About the Role At Hinge, the recommendation engine is a central part of our product. Every interaction users have with each other on our app begins with the systems your team builds and owns. As the engineering manager of this team, you will help drive the strategy and execution behind the infrastructure and features that power our recommendations. You’ll work closely with machine learning engineers, product managers, data scientists, and data engineers to build systems that balance personalization, fairness, and user experience at scale, from low-latency match-serving pipelines to the candidate retrieval and ranking systems that determine who users see and when. Our ability to provide good recommendations is central to achieving trust, engagement, and, most importantly, whether people can find who they’re looking for on Hinge. Responsibilities * Lead, mentor, and grow a team of 6-8 engineers building recommendation services * Partner with ML to productionize recommendation models and ensure low-latency, high-availability serving infrastructure * Own the technical roadmap for the recommender platform, balancing new capabilities with reliability and performance improvements * Drive architecture decisions for recommendation and search infrastructure * Establish and maintain engineering standards for code quality, testing, observability, and incident response * Collaborate with Product, Design, and cross-functional engineering teams to define and deliver product-facing recommendation features * Manage hiring, performance reviews, career development, and team culture What We're Looking For * 8+ years of software engineering experience, with 4+ years in an engineering management role * Strong backend systems expertise – you've built or operated large-scale distributed systems in production * Experience with recommendation systems, search ranking, personalization, or adjacent ML-serving infrastructure * Proficiency in one or more backend languages (ideally Go) * Familiarity with data processing architectures, feature stores, and model-serving technologies (e.g., Kafka, Spark, ElasticSearch, etc) * Track record of hiring, developing, and retaining high-performing engineering teams * Ability to communicate technical trade-offs clearly to both engineers and non-technical stakeholders Nice to Have * Experience with ML frameworks (TensorFlow, PyTorch) or MLOps tooling (MLflow, Kubeflow, Airflow) * Hands-on experience with cloud infrastructure (AWS, GCP, or Azure) and container orchestration (Kubernetes) * Background in A/B testing and experimentation platforms * Prior work at scale (millions of daily active users or equivalent throughput) Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary range is reflective of a position based in New York City. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting.As a member of our team, you’ll enjoy: 401(k) Matching: We match 100% of the first 10% of pre-tax 401(k) contributions you make, up to a maximum of $10,000 per year. Professional Growth: Get an annual Learning & Development stipend once you’ve been with us for three months. You also get free access to Udemy, an online learning and teaching marketplace with over 6000 courses, starting your first day. Parental Leave & Planning: When you become a new parent, you’re eligible for 100% paid parental leave (20 paid weeks for both birth and non-birth parents.) Fertility Support: You’ll get easy access to fertility care through Carrot, from basic treatments to fertility preservation. We also provide a stipend towards fertility preservation. You and your spouse/domestic partner are both eligible. Date Stipend: All Hinge employees receive a $100 monthly stipend for epic dates– Romantic or otherwise. Hinge Premium is also free for employees and their loved ones. ERGs: We have eight Employee Resource Groups (ERGs)—Asian, Unapologetic, Disability, LGBTQIA+, Raices, Women/Nonbinary, Parents —that hold regular meetings, host events, and provide dedicated support to the organization & its community. At Hinge, our core values are… Authenticity: We share, never hide, our words, actions and intentions. Courage: We embrace lofty goals and tough challenges. Empathy: We deeply consider the perspective of others. Diversity inspires innovation Hinge is an equal-opportunity employer. We value diversity at our company and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We believe success is created by a diverse workforce of individuals with different ideas, strengths, interests, and cultural backgrounds. If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please let your Talent Acquisition partner know. #Hinge .

Job DescriptionRole Description We're looking for a talented and ambitious machine learning engineer with 5+ years of experience building production AI systems who's excited to tackle one of the toughest challenges in healthcare: automatically resolving claim denials. You'll be the technical lead for their agentic AI platform that autonomously researches, understands, and resolves insurance claim denials, helping healthcare practices recover millions in lost revenue. Insurance claim denials cost healthcare practices $125 billion annually, and resolving them requires deep expertise in medical billing, payer rules, and claim documentation. Today, billing managers spend hours manually researching each denial, gathering supporting documentation, and crafting appeals. We're building an agentic AI system that automates this entire workflow - from denial classification and root cause analysis, to evidence gathering and appeal letter generation. As a machine learning engineer, you'll architect and build the intelligent agents that power this system. You'll design multi-agent workflows that collaborate to interpret complex denial reasons, retrieve relevant clinical and billing information through RAG systems, reason about payer policies, and generate compelling appeals. This is a greenfield opportunity to build a production agentic system that will directly impact the financial health of healthcare practices. you can You should be comfortable (and excited!) about working in a fast-paced, early-stage startup environment where you can wear many hats and take on new challenges as they arise. This is a great opportunity for someone who wants to work on a highly challenging project at the intersection of AI and healthcare. THIS ROLE IS FULL-TIME. We're looking for candidates based in NYC. NO RELOCATION What you'll do • Design and build the architecture for our agentic AI system that autonomously resolves insurance claim denials, • Develop specialized AI agents for denial classification, root cause analysis, evidence retrieval, policy reasoning, and appeal generation, • Implement multi-agent orchestration frameworks that coordinate complex workflows across research, decision-making, and document generation, • Build and optimize RAG systems to retrieve relevant clinical documentation, billing records, and payer policy information, • Create evaluation frameworks and feedback loops to continuously improve agent performance and reliability, • Design prompt engineering strategies and fine-tuning approaches to optimize LLM behavior for healthcare billing workflows, • Work closely with billing managers to understand denial resolution workflows and translate them into agent behaviors, • Collaborate with the engineering team on production infrastructure for deploying and monitoring AI agents at scale, • Actively contribute to building the team's AI/ML vision and technical roadmap, • Collaborate on code reviews and technical design documents to ensure code quality and distribute knowledgeWe’d love to hear from you if…, • You’re passionate about Healthcare AI/ML – you want to solve real, pressing problems for providers and put them in control of their businesses. You naturally empathize with users and enjoy designing solutions with their needs in mind., • You’re excited to shape the future of our engineering team and lead by example – as an early team member, you’ll have the chance to influence everything from our technical roadmap to our company culture. You have a radical sense of ownership with the ability and desire to own technical roadmaps and refine ambiguous problems. You also have a low ego, a growth mindset, and a desire to see the product and team scale with your impact., • You have a love for your craft and strong technical execution - You view coding as a craft, not just a task, and you're excited about using technology to create meaningful impact. Your technical skills go beyond coding; you care about building a product that works at scale, with the user at the forefront. Must have 5+ years of experience in machine learning engineering, with a focus on building production AI systems and deploying models at scale. Strong experience with machine learning frameworks (PyTorch, TensorFlow, or JAX) Experience working with healthcare data or understanding of medical billing workflows is a plus Must be Proficiency in: • Python and modern ML frameworks (PyTorch, TensorFlow, or JAX), • LLM technologies, including prompt engineering, fine-tuning, and RAG systems, • Vector databases and semantic search systems, • Building reliable, production-grade AI systems with proper evaluation and monitoring, • MLOps practices, including model versioning, A/B testing, and performance tracking Joining a meaningful team means the opportunity to make a direct, meaningful impact on clinicians' lives and the financial health of their practices. Here’s what you can expect from working with us: Meaningful Impact You’ll be tackling one of the most complex challenges in healthcare, helping practices thrive in a chaotic financial landscape. Your work will directly help solve one of the most hair-on-fire problems for providers, ensuring they can focus on what they do best: caring for patients. Autonomy & Ownership As an early team member, you’ll have significant autonomy and the chance to shape our company from the ground up. You’ll have ownership over your work and the freedom to challenge the status quo in an environment that values initiative and creativity. Growth & Learning We’re a small, ambitious team with big goals, which means you’ll be constantly learning and growing. You’ll take on new challenges, expand your skill set, and have direct access to experienced founders and advisors who are invested in your development. We also offer stipends for professional development courses & books (which we often take together!) so we can all continue to grow.

Job Description Project Overview HireScale is partnering with an innovative organization looking to accelerate their AI capabilities and embed intelligent systems into core workflows. This engagement is built around rapid 0→1 product development—taking ideas from concept to working prototypes and MVPs with speed, precision, and real-world applicability. The focus is on shipping, not speculating. You’ll leverage AI-assisted development as a force multiplier—using modern tooling to compress build cycles, iterate quickly, and validate ideas in-market—without compromising on code quality, system design, or long-term scalability. This is a hands-on role for a consultant who can operate across the full lifecycle: • Rapidly translating ambiguous ideas into tangible prototypes, • Building MVPs that balance speed with solid engineering fundamentals, • Making smart trade-offs between velocity and technical rigor, • Establishing patterns that can evolve from prototype → production You’ll work at the intersection of product, engineering, and AI—bringing structure to fast-moving environments while maintaining a high bar for accuracy, performance, and maintainability. The end goal isn’t just to build something quickly—it’s to build the right thing, prove it works, and set the foundation to scale it. Scope of Work & Core Capabilities • Design and ship AI-driven solutions aligned to clear business outcomes, • Translate ambiguous use cases into fast, working prototypes and MVPs, • Build, test, and deploy scalable AI applications end-to-end, • Apply strong engineering fundamentals to balance speed, accuracy, and maintainability, • Optimize models, pipelines, and system performance for production readiness, • Leverage modern AI/ML frameworks and LLMs (OpenAI, Anthropic, LLaMA, Mistral), • Develop across Python, JavaScript/TypeScript, and SQL-based environments, • Utilize frameworks like LangChain, LlamaIndex, PyTorch, TensorFlow, FastAPI, and Node.js, • Deploy and manage infrastructure across AWS, GCP, or Azure using Docker and modern hosting platforms (Vercel, Netlify), • Work with vector databases and data systems (PostgreSQL, Pinecone, Weaviate, FAISS), • Collaborate with stakeholders and communicate complex concepts clearly, • Document solutions and enable clean handoff for internal teams Engagement Brief This consulting engagement is focused on delivering real, production-ready AI outcomes within a defined timeframe by balancing speed, scalability, and measurable business impact. It’s structured for experienced builders who can own execution end-to-end and deliver work that lasts beyond the engagement. • Target Outcomes: Production-ready AI solutions aligned to defined use cases, delivering measurable improvements in efficiency, accuracy, or cost, with scalable architecture and a clean handoff for internal teams, • Duration: 8–12 weeks, with potential extension based on outcomes, • Commitment: Full-service or fractional, depending on scope, • Budget: Flexible based on timeline, scope, and proposal, • Start Date: ASAP Portfolio Requirements: • 2–3 relevant AI/ML projects (production or near-production), • Demonstrated end-to-end ownership (problem → solution → outcome), • Clear evidence of impact (metrics, business results, or adoption), • Supporting materials such as GitHub, case studies, or technical write-ups preferred About HireScale HireScale is redefining how people and organizations grow and work together. We connect companies with top-rated independent consultants to build agile, highly skilled and resilient teams; while also empowering talent to shape their own paths and align meaningful work with personal freedom and purpose. Our goal is a future where opportunity is open, work is self-directed, and everyone thrives.

Job Description Mirage is an AI-native video platform that intelligently orchestrates production and editing through natural language. Our models leverage contextual awareness to execute the same creative decisions a professional editor would — dramatically improving productivity for experienced teams, while making video creation accessible to anyone. We’re an interdisciplinary team addressing some of the most difficult technical and creative challenges in generative media. As an early member of our team, you’ll tackle foundational problems that remain largely unsolved across the industry, driving an outsized impact on the future of creative expression. More about us Product (Captions by Mirage) Research (Seeing Voices, technical-white-paper) Updates (Mirage on X / twitter) TechCrunch, Forbes AI 50, Fast Company (press) Our Investors We’re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, General Catalyst, Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more. Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square) About the Role Mirage is seeking a Research Engineer to build and scale systems for training and deploying large language models for multimodal creative tasks, specifically focusing on video analysis pipelines. You’ll work closely with researchers to turn ideas into high-performance systems that power new product capabilities. This role emphasizes efficiency, scalability, and robustness across the full LLM lifecycle. Responsibilities * Build pipelines for large-scale LLM training and fine-tuning, optimizing data loaders for high-bandwidth multimodal datasets * Optimize training and inference performance * Implement distributed systems for scalable experimentation * Improve latency, throughput, and cost efficiency for complex multimodal inputs and structured generation * Support deployment of LLM systems into production environments * Develop tools for evaluation, monitoring, and iteration What makes you a great fit * 2+ years of professional industry experience * Strong experience with large-scale ML systems * Proficiency in PyTorch, CUDA, Triton, and distributed training * Experience optimizing LLM training or inference * Strong systems intuition (memory, compute, throughput tradeoffs) * Ability to bridge research and production * Strong software engineering and debugging skills Benefits: * Comprehensive medical, dental, and vision plans * 401K with employer match * Commuter Benefits * Catered lunch multiple days per week * Dinner stipend every night if you're working late and want a bite! * Grubhub subscription * Health & Wellness Perks * Multiple team offsites per year with team events every month * Generous PTO policy Captions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please note benefits apply to full time employees only. Compensation Range: $175K - $275K

Job Description About impact.com impact.com is the world's leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L'Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results. Your Role at impact.com: We're seeking a Senior Data Scientist to serve as an embedded Data Scientist within our Programmatic Experience Group. You'll own the design and deployment of machine learning models that optimize yield, pricing, and inventory allocation at scale — sitting at the intersection of data science, platform engineering, and marketplace economics. This is a high-craft, high-ownership individual contributor role. You'll work end-to-end: architecting the data pipelines that feed your models, engineering the features that drive performance, and deploying real-time inference systems that make decisions at speed. Your work directly determines how effectively Impact's programmatic marketplace balances advertiser performance with publisher monetization — making this one of the highest-leverage technical roles in the business. You'll collaborate closely with Product, Data Science, and Programmatic Delivery Engine Engineering, but you operate with significant autonomy. You're expected to bring both the modeling rigor of a data scientist and the production instincts of an ML engineer — and to be genuinely excited about both. What You'll Do: Yield Optimization & Pricing Models • Design and deploy ML models that optimize auction pricing, bid shading, floor price setting, and yield across Impact's programmatic inventory., • Build and iterate on real-time pricing algorithms that balance short-term revenue efficiency with long-term publisher and advertiser health., • Develop and maintain feedback loops that allow pricing models to adapt to shifting market conditions, inventory mix, and demand patterns., • Own ML-driven inventory allocation logic: routing, pacing, and matching supply to demand across partner segments, deal types, and campaign objectives., • Build models that forecast inventory availability, demand curves, and clearing prices to support proactive allocation decisions., • Design and own the data infrastructure that feeds programmatic models: event pipelines, feature stores, training datasets, and real-time feature serving., • Engineer high-signal features from auction logs, bid stream data, user signals, contextual attributes, and historical performance — at the scale of programmatic data volumes., • Deploy models to production real-time inference environments; own latency, reliability, and throughput requirements for auction-time decision-making., • Build monitoring systems that track model performance, data drift, and system health in production; define alerting thresholds and retraining triggers., • Partner with MLOps and Platform Engineering to ensure scalable, low-latency serving infrastructure meets SLOs under high-volume auction traffic., • Design and execute rigorous A/B and holdout experiments to measure the causal impact of model changes on yield, fill rate, advertiser performance, and publisher revenue., • Build evaluation frameworks that go beyond offline metrics — validating model behavior in live auction environments where feedback signals are delayed or noisy., • Research and implement adaptive, self-learning components within the programmatic stack — including contextual bandits, reinforcement learning signals, and online learning approaches where appropriate., • Design feedback mechanisms that close the loop between auction outcomes, model updates, and system behavior; reduce reliance on manual tuning and rule-based overrides., • Serve as the primary ML technical partner for the Rubicon product and engineering teams; translate business requirements into modeling approaches and communicate technical tradeoffs clearly., • Collaborate with Data Science peers on shared infrastructure, modeling standards, and cross-domain feature reuse. Required • Experience: 5+ years in data science, ML engineering, or quantitative research, with at least 2+ years building and deploying ML models in programmatic advertising, ad tech, marketplace optimization, or a closely related domain (e.g., real-time bidding, dynamic pricing, auction systems)., • Programmatic & marketplace depth: Demonstrated understanding of programmatic auction mechanics (RTB, header bidding, floor pricing, deal types, bid shading) and how ML can be applied to optimize outcomes across the supply-demand stack., • Production ML engineering: Proven ability to take models from prototype to production independently — including real-time inference, monitoring, retraining pipelines, and SLO ownership., • Data architecture: Experience designing and building data pipelines, feature stores, and training infrastructure for high-volume, low-latency ML systems., • Technical skills:, • Strong Python and SQL; proficiency with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow) and large-scale data tools (Spark, Kafka, or equivalent streaming/batch frameworks)., • Experience with real-time feature serving and low-latency model deployment (REST APIs, gRPC, or streaming inference)., • Familiarity with production ML workflows: model versioning, drift monitoring, A/B testing, evaluation, and retraining., • Experience processing and modeling at programmatic data scale: high-cardinality auction logs, bid stream data, impression and click events., • Experimentation rigor: Strong grasp of causal inference and experiment design in online, delayed-feedback environments (auction holdouts, switchback tests, variance reduction techniques)., • Communication: Ability to explain complex modeling decisions and tradeoffs to Product and business stakeholders; comfortable presenting in cross-functional forums., • Direct experience with SSP, DSP, or exchange-side yield optimization — particularly floor price optimization, bid landscape modeling, or deal matching algorithms., • Familiarity with auction theory (first-price vs. second-price dynamics, optimal reserve pricing, revenue equivalence) and its practical implications for programmatic ML., • Experience with contextual bandits, multi-armed bandits, or reinforcement learning applied to real-time decisioning problems., • Knowledge of online learning and adaptive algorithms in production environments with non-stationary data distributions., • Familiarity with privacy-preserving ML techniques relevant to programmatic (differential privacy, federated learning, cookieless attribution modeling)., • Experience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub) and/or Databricks/Spark for large-scale event processing and model training., • Exposure to supply forecasting, inventory management, or capacity planning in programmatic or marketplace contexts., • Marketplace intuition. You understand programmatic auctions not just as an engineer but as an economist — you think about incentive structures, equilibrium dynamics, and how model decisions ripple through the supply-demand stack., • Full-stack ML ownership. You're as comfortable designing a feature store schema as you are tuning a gradient boosting model or debugging a latency spike in production. You own the whole chain., • Feedback loop thinking. You don't just deploy models — you design the systems that make them smarter over time. You think about how today's decisions become tomorrow's training signal., • Rigor under real-world constraints. You know how to run clean experiments in environments where feedback is delayed, data is noisy, and business pressures create tradeoffs. You don't let imperfect conditions become an excuse for imprecise thinking., • Pragmatic delivery. You ship. You balance the perfect with the production-ready, iterate fast, and know when an MVP outperforms a six-month research project. *This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Benefits and Perks: At impact.com, we believe that when you're happy and fulfilled, you do your best work. That's why we've built a benefits package that supports your well-being, growth, and work-life balance. • Medical, Dental, and Vision insurance, • Office-only catered lunch every Thursday, a healthy snack bar, and great coffee to keep you fueled, • Flexible spending accounts and 401(k), • Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life., • Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health., • A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval., • Investing in Your Growth: We're committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses., • Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver. #LI_NewYork_NewYork

Job DescriptionDescriptionHeadquartered in Kendall Square, Cambridge (MIT), C10 Labs is expanding its presence to New York City - one of the most vibrant ecosystems for Applied AI. As we grow, we are seeking bold, entrepreneurial leaders to help shape the future of AI innovation. Press Release Position Overview: We are seeking a part-time AI Fellow to join our team in a part-time capacity. This position is more than a job - it's an opportunity to shape the future of AI, molding our portfolio companies into global leaders in the AI space. This role offers a hands-on opportunity to work on challenging projects, collaborate with experienced researchers and engineers, and contribute to the development of groundbreaking AI solutions. If you value working with the brightest minds in the world in areas like climate tech and health then come join us to shape the future of humanity! What you'll do: • Define and lead AI initiatives within our portfolio companies, working closely with founders and tech teams., • Oversee the application of AI technologies across multiple platforms and products., • Share knowledge and insights through regular presentations, workshops, and collaboration sessions with venture and portfolio teams., • Advise on best frameworks and tools for our portfolio companies to create solutions., • Advise our executive team on AI strategy, risks, opportunities, and investments., • Product Development Experience: full product development and bringing cutting edge AI products, platforms, and services to market, • Technical Development: Expertise in AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, and others. Strong programming full stack skills in languages such as Python, R, or Java, with experience in implementing machine learning models and algorithms., • Knowledge of cloud platforms (e.g., AWS, Google Cloud, Azure) for deploying AI solutions at scale., • Familiarity with AI model optimization, including hyperparameter tuning, model evaluation, and performance benchmarking., • Major plus will be experience with assessing tech readiness in AI projects using commonly used frameworks like TRL, AI Maturity Models, Model Validation Frameworks, SAFE AI, IEEE, IRL., • An exciting opportunity to shape the AI landscape and create industry-defining companies., • Collaborative, innovative, and intellectually stimulating work environment., • Exposure to real-world AI projects and applications., • A platform to leverage your AI expertise and make a global impact. If you are passionate about AI, would love to work with an amazing team, ready to solve challenging problems, and eager to transform industries through innovative technologies, we want to hear from you. Apply now and join us on our mission to shape the future of AI. C10 Labs is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Job DescriptionAbout CookUnity: Food has lost its soul to modern convenience. And with it, it has lost the power to nourish, inspire, and connect us. So in 2018, CookUnity was founded as the first-of-its-kind platform that connects the world with the source of truly great food: chefs. Today, CookUnity delivers 50 million meals a year from the industry's best chefs to homes all over the country. Fresh. Ready-to-eat. And crafted with the passion that nourishes body and soul. Unwilling to stop there, CookUnity is expanding beyond delivery to become an ever-innovating marketplace focused on our singular mission: empower Chefs to nourish the world. If that mission has you hungry in more ways than one, you've found the right job posting. About the Role We're hiring for an experienced ML-focused Data Scientist to own growth-oriented modeling across the customer lifecycle - acquisition, activation, retention, resurrection and monetization. You'll work alongside other data scientist to design, validate, and productionize statistical and ML systems (pLTV, churn/survival, uplift/incrementality, lookalikes, clustering/embeddings, NBA/ranking) that directly drive growth. This is a hands-on role for someone with strong mathematical/statistical foundations, broad modeling experience, and pragmatic MLOps chops who can lead experiments and partner closely with Marketing, Engineering, CRM, and Product. What you'll do… • Lifecycle modeling: Build and maintain predictive LTV, churn (including survival/time-to-event), order-rate, and resurrection models that feed acquisition, CRM, and retention strategies., • Acquisition & lookalikes: Create lookalike / propensity models for paid channels and audience construction; optimize CAC vs LTV tradeoffs., • Next-Best-Action & personalization: Develop NBA/ranking models, small-scale recommenders and embedding-based similarity systems to increase activation and orders., • Unsupervised & representation learning: Lead segmentation, clustering, embeddings and representation work that create actionable cohorts and features., • Production & MLOps: Own the full model lifecycle - training pipelines, CI/CD, model registries, containerized deployment, monitoring, retraining and drift detection; partner with engineers to operationalize models into CRM, marketplace and paid channels., • Model governance & reproducibility: Ensure models are well-tested, explainable, calibrated, and auditable; document assumptions, limitations and business mappings., • Cross-functional influence: Translate technical work into product recommendations, dashboards and clear narratives for Growth, Marketing and Engineering. Mentor peers and raise modeling and MLOps standards.Required qualifications, • 5-8+ years in data science, applied ML or statistics, with a track record of shipping production models., • Strong math & statistics: probability, inference, regression, survival analysis/time-to-event, causal reasoning, and familiarity with statistical modeling tradeoffs., • End-to-end ML experience: experience building, validating and deploying classification/regression/ensemble/deep models; comfort with embeddings and representation learning., • MLOps & production skills: pragmatic experience with model CI/CD, model registries (MLFlow or similar), containerization (Docker), orchestration (Airflow), and runtime infra (K8s / ECS)., • Software engineering & tooling: Python (pandas, scikit-learn, XGBoost/LightGBM, PyTorch/TensorFlow optional), strong code hygiene, testing and reproducibility., • Product & stakeholder collaboration: excellent communication, ability to embed with Growth/CRM/Marketing and translate models into product decisions., • Education: BS in a quantitative field required; MS/PhD in statistics, math, CS, economics or similar preferred.Nice-to-haves, • Experience in subscription marketplaces, food-tech, or consumer marketplaces., • Familiarity with feature stores, Snowflake/BigQuery, and production monitoring tools., • Experience with causal libraries (EconML), uplift frameworks, or survival modeling packages., • Prior work on small-scale recommender systems, embeddings, or NLP personalization. Learn More About CookUnity We believe great leadership starts with alignment on vision, values, and ways of working. To give you deeper insight into who we are and what we're looking for, we invite you to explore: CookUnity's Leadership Principles – The values and behaviors that guide how we operate, collaborate, and scale. We hope this provides valuable insight into our culture and product vision. If this excites you, we'd love to connect! Benefits 🩺 Health Insurance coverage 🌅 401k Plan ⛱ Unlimited PTO 🗓️ 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical 🐣 Paid Family leave 🕯 Compassionate Leave: 3-5 days each time the need arises 🥘 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly 🧘🏽️‍♀️ Wellness perks: access to a nutritional coach and fitness subsidies to build a healthy lifestyle 👩🏾️‍🏫 Personalized Spanish coach 🌟 Awesome opportunity to join a company that is looking to change how we eat and how chefs work! Compensation All final pay rates will be determined by candidates experience, knowledge, skills, and abilities of the applicant, internal equity, and alignment with market data.Pay Range for this position$160,000—$185,000 USD If you're interested in this role, please submit your application, and if we think you might be a fit, we'll get in touch with you. Thank you for your time! CookUnity is an Equal Opportunity Employer. We are dedicated to creating a community of inclusion and an environment free from discrimination or harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity, national origin, citizenship status, protected veteran status, genetic information, or physical or mental disability. A quick note for all candidates We've recently seen an increase in recruitment scams across the industry, and we want to make sure you (and your data) stay safe while applying to CookUnity. We also want you to know that we take this seriously — sometimes, as part of our process, we may ask for a brief "proof of humanity" to confirm that we're connecting with a real person, not an impersonator. Here are a few tips to help you protect yourself and know what to expect from us: • Apply only through our official channels. All open roles are listed on our official careers page: careers.cookunity.com, • Our recruiters are real people — and easy to verify. You can always find them on LinkedIn with verified profiles. If you're unsure, feel free to reach out to us on our official LinkedIn Company Page., • We only communicate through official CookUnity channels. That means emails ending in @cookunity.com and interviews held through official company platforms (Google Meet or Zoom) — never WhatsApp, Telegram, or SMS.

Job Description Basic Qualifications: • Knowledge of different compilation steps (and ability to fix) in languages such as Go, C, C++, or Java., • Excellent communication skills and the ability to collaborate effectively with cross-functional teams, • Ability to mentor and grow a group of other Software Engineers, • Ability to lead projects with several cross-org dependencies and design complexities, • Large-scale training using data structures and algorithms, • Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning) Preferred Qualifications • PhD or equivalent in Computer Science, Engineering, Mathematics or related field, • 8+ years of experience in professional software development experience, developing and deploying systems in production environments, • Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib, • Excellent communication skills and the ability to collaborate effectively with cross-functional teams, • Ability to mentor and grow a group of other Software Engineers, • Anomaly Detection Techniques, • Deep Learning, • Scalable ML architecture, • Feature management, • Causal ML, • Reinforcement learning Anticipated base 250-280k + bonus + equity and comprehensive benefits

Job Description Applied Physics is seeking a highly motivated and skilled professional to join our Machine Learning team at the Advanced Propulsion Laboratory at Applied Physics. In this role, you will have the opportunity to work on cutting-edge research in new and emerging fields. Responsibilities: • Conduct research on state-of-the-art Machine Learning algorithms relevant to the problem being addressed., • Implement, train, and validate proposed algorithms for specific problem domains., • Contribute to the integration of algorithms within larger programmatic systems that require these capabilities., • Collaborate with others in a multidisciplinary team environment to accomplish research goals., • Pursue both independent and collaborative research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory., • Publish research results in peer-reviewed scientific journals and present results at conferences, seminars, and meetings., • PhD in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics, or another technical discipline providing an underlying skillset in data analysis and Machine Learning techniques., • Fundamental knowledge of and/or experience developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, representation learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, ensemble methods, statistical modeling and inference (e.g., probabilistic graphical models, Gaussian processes, or nonparametric Bayesian methods)., • Experience in the broad application of one or more higher-level programming languages such as Python, Java, Scala, or C/C++., • Experience with one or more deep learning libraries such as PyTorch, TensorFlow, Keras, or Caffe., • Proven ability to undertake original research and communicate findings in peer-reviewed publications., • Experience working with a multidisciplinary team of scientists, engineers, and project managers to develop and apply these capabilities to inform engineering decisions. We offer a competitive salary and benefits package, flexible work hours, and opportunities for growth and career development. Join our dynamic and passionate team and help us make a positive impact on the world. If you are a talented, motivated, and empathetic individual who shares our passion for making a difference, we encourage you to apply for this exciting opportunity to work with our team at Applied Physics. Applied Physics is an equal opportunity employer.

Job Description Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales — from molecules to organisms — enabling us to predict, understand, and program living systems in ways never before possible. Output Biosciences is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI and biology, and backed by top VCs including Y Combinator. As a Machine Learning Research Scientist, Interpretability, you'll work alongside our founders and team members to develop AI systems capable of processing and reasoning across multiple biological data modalities simultaneously. * You will develop specialized methods for understanding our biological reasoning models, reverse-engineering how they represent and process complex biological information. * You will design and conduct experiments to uncover interpretable features across biological scales. * You will address unique challenges in biological model interpretation, such as disentangling the multi-scale, hierarchical representations of biological systems * You will build biology-specific visualization tools that can map model activations to meaningful biological concepts. Who We're Looking For: * You have a Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Physics, or a relevant technical field. * You have a PhD with 2 years of research experience, or a Bachelor's degree with 4+ years of research or industry experience in Deep Learning, Artificial Intelligence, or other relevant fields. * You have a strong publication record in top-tier AI conferences or journals (e.g., NeurIPS, ICML, ICLR). * You are proficient in Python and have expertise in at least one major deep learning framework (PyTorch, TensorFlow, or JAX). Who You Are: * You have excellent problem-solving skills and the ability to quickly adapt to new challenges. * You exhibit a proactive approach to problem-solving, thinking beyond the specific task, taking ownership of challenges, and taking pride in solving them. * You have a mature mindset in ambiguous situations, helping to frame questions and seek clarity while making decisions in the face of uncertainty. * You have excellent communication skills and can clearly articulate complex technical concepts. * You are motivated by making a real impact and are committed to tackling problems of significant consequence with determination and creativity. Bonus points: * You have experience applying machine learning to biological or chemical problems. * You have knowledge of physics, molecular biology, chemistry, computational biology, bioinformatics, cheminformatics, or related fields. * You have experience with multi-modal learning. * You have contributed to open-source machine learning projects/ * You have experience in developing efficient code in C/C++. Our Values ❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions. 🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards. 🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community. 📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner. 🎮 Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling. What We Offer * We encourage new and different ideas, creativity and contrarian thinking * Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you * You own your day-to-day management. What we care about is that we all hit our milestones * Competitive salary and equity in a growing, well-funded startup * Excellent medical, dental, and vision coverage Compensation Range: $120K - $250K

Job DescriptionCareer Renew is recruiting for one of its clients an Applied ML Engineer - this is a hybrid role in Arlington, VA or Boston, SF Bay Area or NY. This role will require a security clearance. Salary range:190-250K USD yearly plus benefits plus equity. We are seeking a versatile and pragmatic Applied ML Engineer to contribute across a broad range of machine learning and perception tasks that power our edge-intelligent maritime systems. 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. Key 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 (Preferred): * 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.

Job Description Datavant is the data collaboration platform trusted for healthcare. Guided by our mission to make the world's health data secure, accessible and actionable, we provide critical data solutions for organizations across the healthcare ecosystem - including providers, health plans, researchers, and life sciences companies. From fulfilling a single patient's request for their medical records to powering the AI revolution in healthcare, Datavanters are building the future of how data is connected and used to improve health. By joining Datavant today, you're stepping onto a driven and highly collaborative team that is passionate about creating transformative change in healthcare. What We're Looking For We are looking for a motivated Data Scientist to help Datavant revolutionize the healthcare industry with AI. This is a critical role where the right candidate will have the ability to work on a wide range of problems in the healthcare industry with an unparalleled amount of data. You'll join a team focused on deep medical document understanding, extracting meaning, intent, and structure from unstructured medical and administrative records. Our mission is to build intelligent systems that can reliably interpret complex, messy, and high-stakes healthcare documentation at scale. This role is a unique blend of applied machine learning, NLP, and product thinking. You'll collaborate closely with cross-functional teams to: • Design and develop models to extract entities, detect intents, and understand document structure, • Tackle challenges like long-context reasoning, layout-aware NLP, and ambiguous inputs, • Evaluate model performance where ground truth is partial, uncertain, or evolving What You Will Do • Play a key role in the success of our products by developing models for document understanding tasks., • Perform error analysis, data cleaning, and other related tasks to improve models., • Collaborate with your team by making recommendations for the development roadmap of a capability., • Work with other data scientists and engineers to optimize machine learning models and insert them into end-to-end pipelines., • Understand product use-cases and define key performance metrics for models according to business requirements., • 6+ years of experience with data science and machine learning in an industry setting, particularly in designing and building NLP models., • Expertise with Python, • Experience with the latest developments in language models (transformers, LLMs, etc.), • Proficiency with standard data analysis toolkits such as SQL, Numpy, Pandas, etc., • Proficiency with deep learning frameworks like PyTorch (preferred) or TensorFlow, • Industry experience shepherding ML/AI projects from ideation to delivery, • Demonstrated ability to influence company KPIs with AI, • Experience with document layout analysis (using vision or multi-modal approaches)., • Experience with Spark/PySpark, • Experience with Databricks, • Have a strong grasp of technologies upon which our platform is built., • Be independent in reading literature and doing research to develop models for new and existing products., • Have ownership over models internally, communicating with product managers, customer success managers, and engineers to make the model and the encompassing product succeed., • Be a subject matter expert on Datavant's models and a source from which other teams can seek information and recommendations. #LI-BC1 We are committed to building a diverse team of Datavanters who are all responsible for stewarding a high-performance culture in which all Datavanters belong and thrive. We are proud to be an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status. At Datavant our total rewards strategy powers a high-growth, high-performance, health technology company that rewards our employees for transforming health care through creating industry-defining data logistics products and services. The range posted is for a given job title, which can include multiple levels. Individual rates for the same job title may differ based on their level, responsibilities, skills, and experience for a specific job. The estimated total cash compensation range for this role is:$184,000—$200,000 USD To ensure the safety of patients and staff, many of our clients require post-offer health screenings and proof and/or completion of various vaccinations such as the flu shot, Tdap, COVID-19, etc. Any requests to be exempted from these requirements will be reviewed by Datavant Human Resources and determined on a case-by-case basis. Depending on the state in which you will be working, exemptions may be available on the basis of disability, medical contraindications to the vaccine or any of its components, pregnancy or pregnancy-related medical conditions, and/or religion. This job is not eligible for employment sponsorship. Datavant is committed to a work environment free from job discrimination. We are proud to be an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status. To learn more about our commitment, please review our EEO Commitment Statement here. Know Your Rights, explore the resources available through the EEOC for more information regarding your legal rights and protections. In addition, Datavant does not and will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay. At the end of this application, you will find a set of voluntary demographic questions. If you choose to respond, your answers will be anonymous and will help us identify areas for improvement in our recruitment process. (We can only see aggregate responses, not individual ones. In fact, we aren't even able to see whether you've responded.) Responding is entirely optional and will not affect your application or hiring process in any way. Datavant is committed to working with and providing reasonable accommodations to individuals with physical and mental disabilities. If you need an accommodation while seeking employment, please request it here, by selecting the 'Interview Accommodation Request' category. You will need your requisition ID when submitting your request, you can find instructions for locating it here. Requests for reasonable accommodations will be reviewed on a case-by-case basis. For more information about how we collect and use your data, please review our Privacy Policy.

Job Description We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and programming. If you also have knowledge of data science and software engineering, we’d like to meet you. Your ultimate goal will be to shape and build efficient self-learning applications. Responsibilities • Study and transform data science prototypes, • Design machine learning systems, • Research and implement appropriate ML algorithms and tools, • Develop machine learning applications according to requirements, • Select appropriate datasets and data representation methods, • Run machine learning tests and experiments, • Perform statistical analysis and fine-tuning using test results, • Train and retrain systems when necessary, • Extend existing ML libraries and frameworks, • Keep abreast of developments in the field Requirements • Proven experience as a Machine Learning Engineer or similar role, • Understanding of data structures, data modelling and software architecture, • Deep knowledge of math, probability, statistics and algorithms, • Ability to write robust code in Python, Java and R, • Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn), • Excellent communication skills, • Ability to work in a team, • Outstanding analytical and problem-solving skills, • BSc in Computer Science, Mathematics or similar field; Master’s degree is a plus

Job Description The Role Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales - from molecules to organisms - enabling us to predict, understand, and program living systems in ways never before possible. Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator. As a Machine Learning Engineer, you'll work alongside our founders and team members to develop and implement cutting-edge AI systems capable of complex biological reasoning across multiple scales. * You will build foundational models for biology capable of reading and writing biology at scale * You will develop deep generative models for biological applications, exploring innovative architectures to capture the complexities of multi-scale biological systems * You will work on distributed training systems to scale our models to billions of parameters, optimizing for performance and efficiency across multi-GPU and multi-node setups while handling large-scale biological datasets * You will engineer efficient data pipelines to manage and process massive biological datasets, addressing challenges in data loading, splitting, and memory optimization * You will develop and implement robust evaluation frameworks for complex biological models, ensuring data integrity and preventing leakage across dataset splits Who We're Looking For: * You have a Bachelor's in Computer Science, Machine Learning, or a related technical field * You have 3+ years of experience in developing and implementing deep generative learning models * You have experience pre-training models and are proficient in distributed computing environments * You are proficient in Python and have expertise in at least one major deep learning framework (PyTorch, TensorFlow, or JAX) * You have experience with deep learning and generative architectures such as transformers, diffusion models and autoencoders * You are skilled in working with terra-scale datasets and scaling models to billions of parameters * You have a strong understanding of machine learning fundamentals, including various model architectures, optimization techniques, and evaluation metrics * You have experience in designing and implementing efficient data pipelines for processing and managing large datasets * You are experienced in developing robust evaluation frameworks and ensuring data integrity in machine learning projects * You are experienced in code organization, version control, and collaborative software development practices. Who You Are: * You have excellent problem-solving skills and the ability to quickly adapt to new challenges * You exhibit a proactive approach to problem-solving, thinking beyond the specific task, taking ownership of challenges, and pride in solving them * You have a mature mindset in ambiguous situations, helping to frame questions and seek clarity while making decisions in the face of uncertainty * You have excellent communication skills and can clearly articulate complex technical concepts * You are motivated by making a real impact and are committed to tackling problems of significant consequence with determination and creativity Bonus points * You have experience applying machine learning to biology or chemistry * You have contributed to open-source machine learning projects or published research papers in the field of AI/ML * You have experience optimizing machine learning models for high-performance computing environments * You are familiar with ML-Ops practices and tools for managing ML experiments and deployments Our Values ❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions. 🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards. 🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community. 📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner. 🎮 Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling. What We Offer * We encourage new and different ideas, creativity and contrarian thinking * Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you * You own your day-to-day management. What we care about is that we all hit our milestones * Competitive salary and equity in a growing, well-funded startup * Excellent medical, dental, and vision coverage Compensation Range: $110K - $250K

Job Description About impact.com impact.com is the world's leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L'Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results. Your Role at impact.com: We're seeking a Data Scientist to help build the next generation of recommendation systems powering our partnership automation platform. Our ecosystem connects a rich set of entities—advertisers, media publishers, creators, products, and consumers—and the relationships between them are where the real value lives. Your work will help surface the right partnerships, the right products, and the right content across this network at scale. You'll contribute to evolving our recommender stack toward a graph-based architecture leveraging semantic embeddings of entities and their relationships, applying cutting-edge techniques in representation learning, graph ML, and retrieval. The system needs to serve recommendations both in batch and real time, respond to dynamic user inputs, drive measurable value for end users across the platform, and remain reliable as the ecosystem grows. This role is hands-on and end-to-end. You'll own modeling and experimentation work for a defined area of the recommendation stack—from problem framing through productionization—in close partnership with Engineering, Product, MLOps, and Business Stakeholders. You're expected to bring (or actively develop) ML engineering chops so you can take a solution from prototype to production, and to be a relentless user of AI coding agents to multiply your output and accelerate iteration. What You'll Do: Core Responsibilities Multi-entity recommendations across the partnership graph Design, build, and evaluate recommendation models that operate across heterogeneous entities—advertisers, publishers, creators, products, and consumers—and the relationships between them. Frame problems in terms of the partnership graph and apply techniques appropriate to each surface, including candidate generation, ranking, reranking, and personalization. Graph-based modeling & semantic embeddings Contribute to evolving our architecture toward graph-based approaches: learn semantic embeddings of entities and relationships, apply graph neural networks or attention aware graph transformer models where they add value, and build representations that generalize across surfaces and use cases. Stay current with cutting-edge techniques in graph ML, representation learning, and modern recommender architectures, and bring relevant ideas into the platform. Batch and real-time serving Build models and pipelines that serve recommendations in both batch and real-time contexts. Partner with Engineering on retrieval infrastructure, vector search, feature stores, and low-latency serving patterns. Make pragmatic tradeoffs between model sophistication, latency, cost, and freshness based on the surface and use case. End-to-end ML delivery & ML engineering Own the full lifecycle of your work: data and feature design, model development, evaluation, launch, monitoring, and iteration. Build production-grade pipelines, write code that other engineers can extend, and partner with MLOps on reproducibility, observability, and reliability. Use AI coding agents aggressively to accelerate prototyping, refactoring, debugging, and shipping—we expect this to be a core part of how you work, not an occasional aid. Experimentation & measurement Design offline evaluation (offline replay, counterfactual evaluation, holdout sets) and online experiments (A/B tests, holdouts, interleaving) to quantify model impact. Apply appropriate statistical methods, recognize common pitfalls in recommender evaluation (position bias, feedback loops, selection effects), and translate results into clear recommendations for product and engineering partners. Cross-functional collaboration Work closely with Product, Engineering, and Business Stakeholders to translate platform goals into measurable model outcomes. Communicate findings, tradeoffs, and recommendations clearly to both technical and non-technical audiences. Document your work so that models, features, and decisions are understandable and reproducible by others. What You Bring: • 3+ years of experience in data science / applied ML, with a track record of shipping production models that delivered measurable user or business impact., • Strong Python and SQL skills; experience working with large-scale data and distributed compute (Spark/Databricks or equivalent)., • Hands-on experience building recommendation or ranking systems—candidate generation, learning-to-rank, retrieval and reranking, or implicit feedback modeling., • Experience with embeddings and representation learning for users, items, content, or other entities., • ML engineering capability (or strong willingness and demonstrated ability to develop it): you can build, ship, and maintain production pipelines—not just prototypes in notebooks., • Strong experimentation skills: designing and analyzing A/B tests, interpreting results, and communicating findings to stakeholders., • Relentless user of AI coding agents in your day-to-day workflow, with a clear sense of where they accelerate you and where they don't., • Insatiable curiosity about new techniques, architectures, and tools—and a track record of teaching yourself things quickly. You read papers, try new tools, and bring ideas back to the team., • Strong problem-solving instincts and the ability to operate with growing autonomy in ambiguous, evolving spaces.Preferred / Nice to have, • Experience with graph-based ML: graph neural networks (KGAT, transformers or similar), graph-aware retrieval, or knowledge graph embeddings., • Experience with modern deep learning recommender architectures (two-tower, sequence/transformer-based recommenders, multi-task ranking)., • Familiarity with vector search and vector databases (FAISS, ScaNN, Vespa, Milvus, or similar) and approximate nearest neighbor methods., • Experience with real-time ML serving, feature stores (Feast, Tecton, or equivalent), and low-latency inference patterns., • Exposure to contextual bandits, reinforcement learning, or off-policy evaluation in recommendation settings., • Familiarity with PyTorch/TensorFlow and PyTorch Geometric / DGL for graph workloads., • Familiarity with GCP (Vertex AI, BigQuery, Cloud Run) and/or mature MLOps practices (CI/CD for ML, monitoring, drift detection)., • Experience in adtech, martech, e-commerce, or two-sided/multi-sided marketplace recommendations.What Sets You Apart, • You think in terms of user and business outcomes, not just model metrics, and you connect modeling choices to real value delivered through the platform., • You're rigorous about measurement but pragmatic about shipping—able to deliver MVPs and iteratively evolve them into durable production systems., • You're a relentless learner. New papers, new tools, new architectures—you find them, try them, and figure out where they fit. You don't wait to be told what to learn., • You use AI coding agents like a power user: they're a force multiplier in your hands, not a crutch., • You have engineering instincts—you care about code quality, system design, and operability, not just model performance., • You're comfortable with messy data, noisy feedback, edge cases, and ambiguous problem spaces, and you excel at iterative improvement. *This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Benefits and Perks: At impact.com, we believe that when you're happy and fulfilled, you do your best work. That's why we've built a benefits package that supports your well-being, growth, and work-life balance. • Medical, Dental, and Vision insurance, • Office-only catered lunch every Thursday, a healthy snack bar, and great coffee to keep you fueled, • Flexible spending accounts and 401(k), • Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life., • Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health., • A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval., • Investing in Your Growth: We're committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses., • Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver., • Technology Financial Support: We provide a technology stipend to help you set up your home office and a monthly allowance to cover your internet expenses. impact.com is proud to be an equal-opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors. #LI_NewYork

Job Description Job Title: Machine Learning Engineering Director Qualifications: • Hold a Bachelor's degree in a technical field (e.g., computer science, machine learning, mathematics, physics, statistics, econometrics), or equivalent hands-on experience., • Demonstrate coding proficiency in at least one programming language, with a strong preference for Python., • Possess a strong foundation in mathematics, statistics, and machine learning concepts, enabling the development, training, and evaluation of production models and facilitating the comprehension of research papers., • Showcase exceptional communication skills, facilitating the effective conveyance of technical ideas and fostering productive collaborations with business partners., • Exhibit an entrepreneurial mindset and a deep passion for unlocking the potential of Large Language Models (LLMs) and classical machine learning techniques to drive a multi-billion dollar business., • Provide evidence of successful management experience, having effectively led teams of 1-2 machine learning engineers or scientists., • Proficiency in building RESTful APIs, ideally using Flask, FastAPI, or other Python frameworks., • Experience in constructing data pipelines that underpin Machine Learning model development., • Familiarity with Python libraries for machine learning, data manipulation, and mathematics, such as PyTorch, numpy, and pandas.

Job Description The Role Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales - from molecules to organisms - enabling us to predict, understand, and program living systems in ways never before possible. Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator. As a Senior Computational Biologist, you'll work alongside members of our research team and our founders to develop AI systems capable of complex biological reasoning across multiple scales. * You will develop machine learning methods to extend our predictive and generative platform * You will design and execute computational pipelines to validate and prioritized de novo generated molecules using state of the art tools * You will use your deep understanding of biology to design novel therapeutics for hard-to-target proteins with our generative models * You will analyze and integrate large-scale biological datasets * Your work will directly impact the development of our biologically-aware AI platform, transforming the landscape of medicine Make a real tangible impact on millions of lives by pushing the boundaries of AI in biology. Who We're Looking For * You have a PhD in a biological field and strong programming skills in Python * You have experience with computational biology tools such as structure prediction, molecular docking and virtual screening * You have experience working with Protein or Chemical Language Models * You like to work collaboratively in a fast-paced startup environment * You are passionate about using data science to unlock the secrets of biology * You exhibit a proactive approach to problem-solving, thinking beyond the specific task, taking ownership of challenges, and pride in solving them * You have a mature mindset in ambiguous situations, helping to frame questions and seek clarity while making decisions in the face of uncertainty * You have excellent communication skills and can clearly articulate complex technical concepts Bonus Points * You have hands-on experience building AI/ML using PyTorch and Lightning * You have experience with cloud computing platforms like AWS * You have hands-on biology laboratory experience * You have contributed to peer-reviewed publications in computational biology * You have knowledge of machine learning techniques applied to biological data Our Values ❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions. 🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards. 🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community. 📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner. 🎮 Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling. What We Offer * We encourage new and different ideas, creativity and contrarian thinking * Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you * You own your day-to-day management. What we care about is that we all hit our milestones * Competitive salary and equity in a growing, well-funded startup * Excellent medical, dental, and vision coverage Compensation Range: $150K - $250K

Job DescriptionAbout Fusemachines Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government.Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.Salary Range: US$ 140,000-190,000/yearRole Overview We’re hiring a mid-to-senior Machine Learning Engineer / Data Scientist to build and deploy machine learning solutions that drive measurable business impact. You’ll work across the ML lifecycle—from problem framing and data exploration to model development, evaluation, deployment, and monitoring—often in partnership with client stakeholders and internal delivery teams. You should be strong in core data science and applied machine learning, comfortable working with real-world data, and capable of turning modeling work into production-ready systems. Key Responsibilities • Problem Framing & Stakeholder Partnership, • Translate business questions into ML problem statements (classification, regression, time series forecasting, clustering, anomaly detection, recommendation, etc.)., • Collaborate with stakeholders to define success metrics, evaluation plans, and practical constraints (latency, interpretability, cost, data availability)., • Data Analysis & Feature Engineering, • Use SQL and Python to extract, join, and analyze data from relational databases and data warehouses., • Perform data profiling, missingness analysis, leakage checks, and exploratory analysis to guide modeling choices., • Build robust feature pipelines (aggregation, encoding, scaling, embeddings where appropriate) and document assumptions., • Model Development (Core ML), • Train and tune supervised learning models for tabular data (e.g., logistic/linear models, tree-based methods, gradient boosting such as XGBoost/LightGBM/CatBoost, and neural nets for structured data)., • Apply strong tabular modeling practices: handling missing data, categorical encoding, leakage prevention, class imbalance strategies, calibration, and robust cross-validation., • Build time series models (statistical and ML/DL approaches) and validate with proper backtesting., • Apply clustering and segmentation techniques (k-means, hierarchical, DBSCAN, Gaussian mixtures) and evaluate stability and usefulness., • Apply statistics in practice (hypothesis testing, confidence intervals, sampling, experiment design) to support inference and decision-making., • Deep Learning, • Build and train deep learning models using PyTorch or TensorFlow/Keras., • Use best practices for training (regularization, calibration, class imbalance handling, reproducibility, sound train/val/test design)., • Evaluation, Explainability, and Iteration, • Choose appropriate metrics (AUC/F1/PR, RMSE/MAE/MAPE, calibration, lift, and business KPIs) and create evaluation reports., • Perform error analysis and interpretation (feature importance/SHAP, cohort slicing) and iterate based on evidence., • Productionization & MLOps (Project-Dependent), • Package models for deployment (batch scoring pipelines or real-time APIs) and collaborate with engineers on integration., • Implement practical MLOps: versioning, reproducible training, automated evaluation, monitoring for drift/performance, and retraining plans., • Documentation & Communication, • Communicate tradeoffs and recommendations clearly to technical and non-technical stakeholders., • Create documentation and lightweight demos that make results actionable.Success in This Role Looks Like, • You deliver models that perform well and move business metrics (revenue lift, cost reduction, risk reduction, improved forecast accuracy, operational efficiency)., • Your work is reproducible and production-aware: clear data lineage, robust evaluation, and a credible path to deployment/monitoring., • Stakeholders trust your judgment in selecting methods and communicating uncertainty honestly.Required Qualifications, • 3–8 years of experience in data science, machine learning engineering, or applied ML (mid-to-senior)., • Strong Python skills for data analysis and modeling (pandas/numpy/scikit-learn or equivalent)., • Strong SQL skills (joins, window functions, aggregation, performance awareness)., • Solid foundation in statistics (hypothesis testing, uncertainty, bias/variance, sampling) and practical experimentation mindset., • Hands-on experience across multiple model types, including:, • Classification & regression, • Time series forecasting, • Clustering/segmentation, • Experience with deep learning in PyTorch or TensorFlow/Keras., • Strong problem-solving skills: ability to work with ambiguous goals and messy data., • Clear communication skills and ability to translate analysis into decisions.Preferred Qualifications, • Experience with Databricks for applied ML (e.g., Spark, Delta Lake, MLflow, Databricks Jobs/Workflows)., • Experience deploying models to production (APIs, batch pipelines) and maintaining them over time (monitoring, retraining)., • Experience with orchestration tools (Airflow, Prefect, Dagster) and modern data stacks (Snowflake/BigQuery/Redshift/Databricks)., • Experience with cloud platforms (AWS/GCP/Azure/IBM) and containerization (Docker)., • Experience with responsible AI and governance best practices (privacy/PII handling, auditability, access controls)., • Cloud certifications: AWS, Google Cloud, Microsoft Azure, or IBM (data/AI/ML tracks), • Databricks certifications (Data Scientist, Data Engineer, or related)Nice-to-Have, • Causal inference experience (e.g., quasi-experimental methods, propensity scores, uplift/heterogeneous treatment effects, experimentation beyond A/B tests)., • Agentic development experience: designing and evaluating agentic workflows (tool use, planning, memory/state, guardrails) and integrating them into products., • Deep familiarity with agentic coding tools and workflows for accelerated product development (e.g., AI-assisted IDEs, code agents, automated testing/refactoring, repo-aware assistants), including strong judgment on quality, security, and maintainability.Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws. Important: Immigration Sponsorship Policy Fusemachines is unable to proceed with candidates who require any form of work authorization or immigration support from the company. This restriction applies to all types of support, including: • Direct Company Sponsorship: Such as H-1B, J-1, or TN visas., • Employer of Record: Listing Fusemachines as the immigration employer on any government documentation. I0GDC3XJwj

Job DescriptionAbout Fusemachines Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government.Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.Salary Range: US$ 140,000-170,000/year Note: We are not considering OTP STEM visas neither H1B support for this roleRole Overview We’re hiring a mid-to-senior Machine Learning Engineer / Data Scientist to build and deploy machine learning solutions that drive measurable business impact. You’ll work across the ML lifecycle—from problem framing and data exploration to model development, evaluation, deployment, and monitoring—often in partnership with client stakeholders and internal delivery teams. You should be strong in core data science and applied machine learning, comfortable working with real-world data, and capable of turning modeling work into production-ready systems. Key Responsibilities • Problem Framing & Stakeholder Partnership, • Translate business questions into ML problem statements (classification, regression, time series forecasting, clustering, anomaly detection, recommendation, etc.)., • Collaborate with stakeholders to define success metrics, evaluation plans, and practical constraints (latency, interpretability, cost, data availability)., • Data Analysis & Feature Engineering, • Use SQL and Python to extract, join, and analyze data from relational databases and data warehouses., • Perform data profiling, missingness analysis, leakage checks, and exploratory analysis to guide modeling choices., • Build robust feature pipelines (aggregation, encoding, scaling, embeddings where appropriate) and document assumptions., • Model Development (Core ML), • Train and tune supervised learning models for tabular data (e.g., logistic/linear models, tree-based methods, gradient boosting such as XGBoost/LightGBM/CatBoost, and neural nets for structured data)., • Apply strong tabular modeling practices: handling missing data, categorical encoding, leakage prevention, class imbalance strategies, calibration, and robust cross-validation., • Build time series models (statistical and ML/DL approaches) and validate with proper backtesting., • Apply clustering and segmentation techniques (k-means, hierarchical, DBSCAN, Gaussian mixtures) and evaluate stability and usefulness., • Apply statistics in practice (hypothesis testing, confidence intervals, sampling, experiment design) to support inference and decision-making., • Deep Learning, • Build and train deep learning models using PyTorch or TensorFlow/Keras., • Use best practices for training (regularization, calibration, class imbalance handling, reproducibility, sound train/val/test design)., • Evaluation, Explainability, and Iteration, • Choose appropriate metrics (AUC/F1/PR, RMSE/MAE/MAPE, calibration, lift, and business KPIs) and create evaluation reports., • Perform error analysis and interpretation (feature importance/SHAP, cohort slicing) and iterate based on evidence., • Productionization & MLOps (Project-Dependent), • Package models for deployment (batch scoring pipelines or real-time APIs) and collaborate with engineers on integration., • Implement practical MLOps: versioning, reproducible training, automated evaluation, monitoring for drift/performance, and retraining plans., • Documentation & Communication, • Communicate tradeoffs and recommendations clearly to technical and non-technical stakeholders., • Create documentation and lightweight demos that make results actionable.Success in This Role Looks Like, • You deliver models that perform well and move business metrics (revenue lift, cost reduction, risk reduction, improved forecast accuracy, operational efficiency)., • Your work is reproducible and production-aware: clear data lineage, robust evaluation, and a credible path to deployment/monitoring., • Stakeholders trust your judgment in selecting methods and communicating uncertainty honestly.Required Qualifications, • 3–8 years of experience in data science, machine learning engineering, or applied ML (mid-to-senior)., • Strong Python skills for data analysis and modeling (pandas/numpy/scikit-learn or equivalent)., • Strong SQL skills (joins, window functions, aggregation, performance awareness)., • Solid foundation in statistics (hypothesis testing, uncertainty, bias/variance, sampling) and practical experimentation mindset., • Hands-on experience across multiple model types, including:, • Classification & regression, • Time series forecasting, • Clustering/segmentation, • Experience with deep learning in PyTorch or TensorFlow/Keras., • Strong problem-solving skills: ability to work with ambiguous goals and messy data., • Clear communication skills and ability to translate analysis into decisions.Preferred Qualifications, • Experience with Databricks for applied ML (e.g., Spark, Delta Lake, MLflow, Databricks Jobs/Workflows)., • Experience deploying models to production (APIs, batch pipelines) and maintaining them over time (monitoring, retraining)., • Experience with orchestration tools (Airflow, Prefect, Dagster) and modern data stacks (Snowflake/BigQuery/Redshift/Databricks)., • Experience with cloud platforms (AWS/GCP/Azure/IBM) and containerization (Docker)., • Experience with responsible AI and governance best practices (privacy/PII handling, auditability, access controls)., • Cloud certifications: AWS, Google Cloud, Microsoft Azure, or IBM (data/AI/ML tracks), • Databricks certifications (Data Scientist, Data Engineer, or related)Nice-to-Have, • Causal inference experience (e.g., quasi-experimental methods, propensity scores, uplift/heterogeneous treatment effects, experimentation beyond A/B tests)., • Agentic development experience: designing and evaluating agentic workflows (tool use, planning, memory/state, guardrails) and integrating them into products., • Deep familiarity with agentic coding tools and workflows for accelerated product development (e.g., AI-assisted IDEs, code agents, automated testing/refactoring, repo-aware assistants), including strong judgment on quality, security, and maintainability.Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws. Important: Immigration Sponsorship Policy Fusemachines is unable to proceed with candidates who require any form of work authorization or immigration support from the company. This restriction applies to all types of support, including: • Direct Company Sponsorship: Such as H-1B, J-1, or TN visas., • Employer of Record: Listing Fusemachines as the immigration employer on any government documentation. pYO5KHk85I

Job DescriptionCareer Renew is recruiting for one of its clients a Staff Backend Engineer - AI - this is an onsite role in NYC. Salary range: 200-250K USD yearly plus benefits plus equity. We build autonomous manufacturing systems powered by AI and robotics to solve America's manufacturing workforce crisis. We're creating the intelligence layer that lets machines run autonomously so manufacturers can scale production without scaling headcount. You'll join a small in-person team in NYC with deep experience from defense tech and AI who've already shipped products to DoD customers. This is your chance to build the future of American manufacturing at the intersection of ML robotics and distributed systems. As Staff ML Backend Engineer you'll own the entire data pipeline for robotics sensor data and build foundational ML infrastructure. You'll make key technical decisions around storage processing and analytics while functioning as a research engineer to keep ML team iteration cycles fast. This Staff Backend Engineer will build the foundational infrastructure for our machine learning pipelines, focusing on creating robust, scalable backend systems for advanced robotics. The role involves owning the data collection and storage pipeline for robotics sensor data, making key technical decisions, and functioning as a research engineer for the ML team to accelerate their iteration cycles. This is a generalist software engineering role focused on the backend, particularly on building production systems for large-scale data and data pipelines, rather than internal tooling. Tech stack Python, Rust, C++, Distributed Systems, Data Pipelines, PyTorch, TensorFlow, Time-series Databases, GPU Requirements: 7+ years of experience in backend engineering building production data pipelines in Python, Rust, or C++ (Mandatory) Built production data pipelines for large-scale sensor/video data. (Mandatory) Experience with distributed systems handling low-latency, high-throughput data flows (Mandatory) Experience in latency-sensitive environments (e.g. trading systems, real-time industrial/robotics systems) (Nice-to-have) BS/MS in Computer Science or a related technical field. (Mandatory) Strong proficiency in Python, Rust, or C++ for backend / systems development (Mandatory) Experience with time-series or streaming data systems (e.g. sensor data pipelines, event streams) (Mandatory) Familiarity with ML infrastructure or supporting ML pipelines in production (not just model training) (Nice-to-have)

Job Description About Us Daat Lab is an AI venture studio that collaborates directly with businesses to transform deep domain expertise into valuable, commercial-grade AI products. We assist companies in identifying and validating high-impact, AI-feasible use cases. Our process spans from initial ideation and building a proof of concept to developing a fully commercializable product and successfully launching it in the market. We maintain an active presence across multiple sectors, including real estate, digital marketing/e-commerce, and health, with an ambitious goal of adding one new product to our portfolio every month. About the Role We are looking for a software engineer to help take concepts from ideas to product. You will work directly with our strategy team and business partners to identify high-value, AI-feasible opportunities, shape product direction, and execute quickly. You’ll own the full product cycle including: discovery, prototyping, building, shipping, and iteration, often across multiple projects at once. This is a hands-on role for someone who thrives in ambiguity, moves fast, and likes being close to customers. What You’ll Do: • Own multiple projects from end to end: brainstorming product concepts, generating POCs to be evaluated and owning builds to reach a minimum viable product., • Build full-stack applications (backend, frontend, data layer, infra, deployment, and monitoring)., • Experiment with AI functionality on each case: classical ML when needed (forecasting, scoring, classification), plus LLM/agent workflows and evaluation loops, • Establish engineering standards: code quality, CI/CD hygiene, logging/analytics, basic security, • You should have:, • 3+ years shipping full-stack products end-to-end, • Strong Python and modern web stack (React/Next.js + APIs + DB + deployments), • Data processing and Machine learning fundamentals (pandas, Sklearn, pytorch/tensorflow, model evaluation), • Experience experimenting with LLMs and Agent frameworks (Open AI SDK, Google ADK, Langchain/Langraph, MCP), • Comfort with ambiguity, fast cycles, and customer-facing iteration, • What Success Looks Like:, • Ship multiple POCs that clearly validate feasibility and ROI, • Salary: $110 - 140k (full-time hire, will start as a 1099 contractor) Please note: Daat Lab is a separate entity, unrelated to Alchemy Worx.

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: MLOps Engineer (JAX, PyTorch, Pallas/Triton) Type: Contract Compensation: $90–$130/hour Location: Remote Role Responsibilities • Guide research and engineering teams to close knowledge gaps and improve AI model performance in MLOps, training infrastructure, and ML framework-level topics., • Design challenging, domain-relevant tasks across multiple specializations. Write accurate and well-structured solutions to MLOps and ML systems problems., • Evaluate MLOps tasks and solutions. Provide clear, written technical feedback., • Develop guidelines and detailed rubrics/evaluation frameworks to assess training pipeline design, distributed systems reasoning, and kernel-level optimization across tasks. Must-Have • 5+ years of dedicated professional experience in ML infrastructure, MLOps, or ML systems engineering at a recognized, top-tier organization., • Hands-on production experience with JAX and/or PyTorch at scale, including distributed training strategies (FSDP, tensor parallelism, pipeline parallelism), memory optimization, and framework-level debugging., • Experience writing or optimizing custom GPU kernels using Pallas (JAX) or Triton, including tiling strategies, memory layout design, and kernel fusion., • Demonstrable career progression., • Ability to engage reliably for at least 30 hours/week during weekdays., • W-2 employment with Cincinnatus LLC., • Upload resume, • AI interview based on your resume

Job DescriptionRadical AI, Inc. is an artificial intelligence company that is accelerating scientific research & development. We are at the forefront of innovation in the field of materials R&D, a critical driver for advancing our most cutting-edge industries and shaping the future. Breaking away from the traditionally slow and costly R&D process, Radical AI leverages artificial intelligence and machine learning to pioneer generative materials science. This innovative field blends AI, engineering, and materials science, revolutionizing how materials are created and discovered. Radical AI's approach speeds up R&D and addresses global challenges, setting new benchmarks in technology and sustainability. The opportunityAs an ML Engineer at Radical AI, you will be responsible for developing machine learning systems, data pipelines, and large-scale training infrastructure. You will orchestrate entire machine learning lifecycles, but also data ingestion, enrichment, model exporting and serving, and much more. Your work will directly impact the development of an end-to-end AI-driven approach to materials discovery and development. Positions are available at various levels of seniority: Senior, Staff, and Principal.Mission • Develop, train, and deploy machine learning models to solve complex problems in materials science and lab automation., • Experiment with cutting-edge ML algorithms and techniques to improve performance and scalability., • Collaborate with researchers on the pre- and post-training stages of model development., • Conduct production-level deployments of our machine learning models and infrastructure., • Continually evaluate model performance and maintain production integrity., • Ensure reproducibility and traceability of models by leveraging version control systems and orchestration tools., • Contribute to research initiatives and participate in knowledge-sharing across teams., • Document workflows, experiments, and deployment procedures for future reference., • Tackle challenging problems with new and different ideas, creativity and contrarian thinking., • Mentor and guide junior team members and interns, promoting an environment of continuous learning and innovation.About you, • Ph.D., M.S., or B.S. in Computer Science, AI, Machine Learning, Applied Maths, Engineering or a closely related field, or equivalent practical experience., • Proven record of accomplishment in building machine learning systems, working with large generative and/or language models, • An excellent understanding of machine learning infrastructure and systems fundamentals., • Strong background in algorithms, data structures, and software engineering principles., • Working knowledge of various generative AI architectures, including transformers, diffusion models, CNFs, and flow matching., • Proficiency in Python and relevant ML libraries (e.g., PyTorch), as well as tools for deploying ML models (e.g., MLflow, K8s, Docker)., • Passion for staying current with the latest trends in AI/ML technologies., • Excellent collaboration and communication skills, capable of articulating complex technical ideas clearly and effectively.Pluses, • Familiarity with distributed computing frameworks such as Ray, Spark, etc., • Strong fundamental knowledge and practical experience using Linux systems, including working with large-scale computing clusters., • Hands-on experience with MLOps tools (e.g., Kubeflow, Seldon, CI/CD pipelines for ML)., • Familiarity with serverless architecture and cost optimization for ML workflows., • Strong publication record in top-tier AI/ML conferences or journals.What we offer, • A competitive compensation package also includes the best in benefits:, • Medical, dental, and vision insurance for you and your family, • Mental health and wellness support, • Unlimited PTO and 14+ company holidays per year, • 401K, • Work closely with a team on the cutting edge of AI research. Disclosure Radical AI is committed to equal employment opportunity regardless of race, color, ancestry, national origin, religion, sex, age, sexual orientation, gender identity and expression, marital status, disability, or veteran status.

Job Description About Synaptrix Labs Inc. Synaptrix is on a mission to revolutionize brain-computer interfaces through non-invasive approaches. We believe that the power to diagnose and treat neurological conditions safely, and to expand human potential, will become a reality with the right fusion of deep learning, signal processing, and computational neuroscience. We're seeking passionate, creative, and technically driven interns to join our team across multiple disciplines: Software Engineering, Hardware Engineering, Machine Learning Research, Industrial Design, and UI/UX Design. If you're excited about building the future of brain-computer interfaces and want to work at the intersection of neuroscience, AI, and human experience, we want to hear from you. Responsibilities: Depending on your background and interests, you may: • Contribute to development of real-time software systems for neural signal processing and data visualization., • Build and prototype non-invasive EEG-based BCI hardware, from electrode arrays to embedded microcontroller systems., • Design, train, and evaluate machine learning models for EEG/EMG decoding, denoising, and signal enhancement., • Develop intuitive interfaces and user experiences for individuals with mobility or communication impairments., • Collaborate with the design team to prototype wearable and ergonomic form factors for next-generation neurotech devices., • Support data collection and analysis in research sessions, assisting with experimental setup and instrumentation., • Participate in cross-functional design reviews and brainstorming sessions that bring together neuroscience, AI, and engineering., • Currently pursuing a Bachelor's or Master's degree in Computer Science, Electrical Engineering, Biomedical Engineering, Neuroscience, Mechanical/Industrial Design, or a related field., • Demonstrated experience with one or more of the following:, • Software: Python, C++, or JavaScript, • Machine Learning: PyTorch, TensorFlow, or JAX, • Hardware: Arduino, PCB design, or embedded systems, • Design: Figma, Fusion 360, SolidWorks, or similar tools, • Strong problem-solving ability and curiosity about neuroscience, AI, or human-machine interfaces., • Excellent communication and teamwork skills; thrives in a fast-paced, interdisciplinary environment., • Prior experience with EEG/EMG systems, biosignal acquisition, or data analysis., • Familiarity with deep learning for time-series or multimodal data., • Experience designing assistive devices, wearables, or medical technology., • Portfolio, GitHub, or research projects demonstrating creative technical work. At Synaptrix Labs, we celebrate curiosity, open collaboration, and scientific rigor. Our interdisciplinary team spans neuroscience, AI, and clinical research, and we are united by the belief that non-invasive BCI is the key to unlocking a new era in healthcare, accessibility, and human augmentation. As an intern, you'll work directly alongside engineers, researchers, and designers who are defining the next generation of brain-computer interfaces. You'll be encouraged to explore bold ideas, experiment freely, and take ownership of meaningful projects from day one. What We Offer: • Hands-on experience in one of the world's most exciting emerging fields: brain-computer interfaces, • Opportunity to contribute to technology that directly improves lives, • Mentorship from scientists, engineers, and founders building real neurotechnology products, • Dynamic NYC workspace blending lab, workshop, and creative studio environments, • Potential for full-time conversion after graduation

Job DescriptionAbout SmartAsset: SmartAsset is an online destination for consumer-focused financial information and advice, whose mission is helping people make smart financial decisions, reaching over an estimated 59 million people each month (as of January 2025) through our educational content and personalized calculators and tools. To extend our mission, we also operate SmartAsset Advisor Marketing Platform (AMP), which helps connect consumers with fiduciary financial advisors.SmartAsset has earned recognition on the Inc. 5000 (#2574 in 2023) and Deloitte Technology Fast 500™ (#250 in 2022) lists. Currently, SmartAsset ranks on Y Combinator's list of Top 100 Companies. A successful $110 million Series D funding round in 2021 valued the company at over $1 billion. *Other than application and licensing fees, SmartAsset did not provide compensation for the aforementioned awards. About the team: The Machine Learning Engineering team designs, builds, and integrates the core platform that unlocks cutting-edge capabilities for financial advisors, including features driven by generative AI. Our engineers are relentlessly evolving this platform, empowering groundbreaking applications and features that truly help financial professionals better connect with their clients and grow their businesses. About the Job: We are seeking a highly motivated and experienced Machine Learning Engineer to join our growing team. In this role, you will be instrumental in crafting and scaling foundational backend systems across predictive systems and generative AI. You will work across the entire software development lifecycle, from architectural design to deployment and ongoing operations, contributing significantly to our core infrastructure and data strategies, and working hand-in-hand with cross-functional partners like LLM Engineers, Product Owners, and Data Scientists to bring our vision to life. Responsibilities: • Design, develop, and maintain high-performance, scalable, and secure backend services, primarily using Python and frameworks like FastAPI, • Translate ambiguous business and technical requirements into concrete software designs and actionable tasks for cross-functional teams, • Work with OLTP databases, including schema design, migration strategies, and performance optimization, • Integrate SmartAsset services with internal and external APIs, including third-party platforms and existing AWS infrastructure, • Ensure secure ingress and egress of data within our private network environments, • Contribute to the design and implementation of our CI/CD pipelines to ensure continual improvements to our cycle time, • Manage and optimize AWS services, including IAM roles and policies, • Gain a deep understanding of how our Python applications integrate with our Kubernetes (EKS) and future ECS-based infrastructure, • Operate and maintain production applications at scale, ensuring high availability, performance, and reliability, • Design and implement data collection pipelines specifically for Large Language Models (LLMs), • Contributed to shared data architecture and data governance practices to ensure the persistence of structured data suitable for analytics and model training, • Explore, integrate, and tune various LLM-related technologies, such as Retrieval Augmented Generation (RAG) systems, and addressing potential scaling challenges, • Investigate and implement agentic technologies, such as tool calling frameworks (e.g., AutoGen), to enhance LLM capabilities, • Proven experience as a ML Engineer with a strong focus on Python development, • Experience with cloud platforms, specifically AWS, including IAM, EKS/ECS, and other core services, • Strong expertise with OLTP/relational databases such as Aurora, Postgres, MySQL etc, • Experience with DevOps toolsets such as Terraform, Open-Telemetry, etc. will be a big plus, • Strong experience in developing and maintaining large-scale, production-grade applications, • Experience in writing clean, maintainable, and testable code following best practices and industry standards, • Experience building integrations with internal and external service providers, • At least 5 years of relevant working experience., • Excellent communication skills, both written and verbal, • Experience with machine learning and deep learning frameworks such as TensorFlow, PyTorch, etc., • Experience with LLMs, RAG, embedding vector databases, or agentic technologies., • Familiarity with productionizing apps built with prototyping frameworks such as Streamlit or Gradio, • Knowledge of data governance and structured data principles, • Prolonged periods of sitting at a desk and working on a computer, • Must be able to communicate via phone calls and/or video conferences (mainly for concierge and sales roles) Available Benefits and Perks:, • All roles at SmartAsset are currently and will remain remote - flexibility to work from anywhere in the Contiguous US., • Medical, Dental, Vision - multiple packages available based on your individualized needs, • Life/AD&D Insurance - basic coverage at 100% company paid, additional supplemental available, • Supplemental Short-term and Long-term Disability, • FSA: Medical and Dependant Care, • 401K, • Equity packages for each role, • Time Off: Vacation, Sick and Parental Leave, • EAP (Employee Assistance Program), • Financial Literacy Mentoring Program, • Pet Insurance California, Colorado, Connecticut, Maryland, Nevada, Rhode Island, Washington, and New York City residents $137,000 - $180,000 + RSUs + benefits. Salary at SmartAsset is determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location within the contiguous United States.

Job Description COMPANY: Canoe Intelligence WEBSITE: TITLE: Sr. Machine Learning Engineer LOCATION: New York City or London (hybrid) / Fully Remote in the United States or United Kingdom SALARY: $180,000 - $220,000 (based on NYC, will be adjusted for geo) The Role: We are looking for a Senior Machine Learning Engineer to design and deploy models that make sense of highly complex, unstructured financial documents, enabling us to deliver data with unprecedented accuracy, speed, and trust. You’ll work hands-on with LLM and other ML Models, helping scale Canoe’s platform while shaping how alternative investment firms interact with their data. What You’ll Do: * Design, train, and evaluate ML models for document classification, entity extraction, summarization, and information retrieval. * Fine-tune and optimize large language models for domain specific use cases, optimizing their performance for accuracy, efficiency, and scalability. * Work closely with data engineering teams to preprocess and engineer features from large datasets to enhance the performance of machine learning models. * Build scalable, production-ready ML services with strong observability, monitoring, and retraining capabilities. * Contribute to Canoe’s MLOps stack, including CI/CD for models, feature stores, evaluation frameworks, and data versioning. * Collaborate with product managers, software engineers, and other stakeholders to integrate machine learning models into end-to-end solutions. * Stay current with advancements in LLMs, Agentic AI, and ML, and translate new research into practical improvements to Canoe’s technology stack. * Conduct code reviews to ensure code quality and provide mentorship to junior members of the machine learning team. What We’re Looking For: * Minimum of 5 years of experience in applied ML engineering, with a focus on NLP, information extraction, or LLMs. * Proficiency in Python and relevant machine learning libraries (e.g., TensorFlow, PyTorch). * Strong understanding of MLOps (Docker, Kubernetes, CI/CD for ML, experiment tracking). * Proficiency with AI-assisted development tools (e.g., GitHub Copilot, Claude Code agent) to accelerate software development, prototyping, testing, and deployment of ML solutions. * Problem-solver with a product mindset and bias toward outcomes. * Excellent communication skills; able to partner across engineering, product, and business teams. * Comfortable in fast-paced, agile startup environments. * Bachelor’s degree in computer science or related field. Preferred * Master Degree or PhD in computer science or related field * Experience in training and deploying large language models. * Familiarity with cloud computing platforms and distributed computing. * Familiarity with modern ML Ops tools such as Modal, Weights and Biases, Sagemaker, etc. * Experience with LLM fine-tuning techniques such as LoRA, QLoRA, or parameter-efficient training frameworks (e.g., Unsloth). * What You’ll Get: * Medical, dental, vision benefits * Flexible PTO * 401(k) * Flexible work from home policy * Home office stipend * Employee Assistance Program * Gym/Wifi reimbursement * Education assistance * Parental Leave Our Values: * Client First —> Listen, and deliver client-centric solutions * Be An Owner —> Take initiative, improve situations, drive positive outcomes * Excellence —> Always set the highest standard for yourself and others * Win Together —> 1 + 1 = 3 Who We Are: Canoe is reimagining alternative investment data processes for hundreds of leading institutional investors, capital allocators, asset servicing firms and wealth managers. By combining industry expertise with the most sophisticated data capture technologies, Canoe’s technology automates the highly-frustrating, time-consuming, and costly manual workflows related to alternative investment document and data management, extraction and delivery. With Canoe, clients can refocus capital and human resources on business performance and growth, increase efficiency, and gain deeper access to their data. Canoe’s AI-driven platform was developed in 2013 for Portage Partners LLC, a private investment firm. Canoe is an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Job DescriptionHinge is the dating app designed to be deleted In today's digital world, finding genuine relationships is tougher than ever. At Hinge, we’re on a mission to inspire intimate connection to create a less lonely world. We’re obsessed with understanding our users’ behaviors to help them find love, and our success is defined by one simple metric– setting up great dates. With millions of users across the globe, we’ve become the most trusted way to find a relationship, for all. About the Role Join Hinge as a Senior Machine Learning Engineer, where you'll lead the application of AI and machine learning to effectively mitigate the impact of bad actors, remove policy violating content, and ensure user safety on the platform. Working closely with an expanding Trust & Safety team, you will collaborate with product managers, data scientists, engineers, and analysts to develop impactful AI/ML solutions. In this high-impact position within a small, dynamic team, you'll have the opportunity to play a foundational role in shaping how Hinge utilizes AI and machine learning in various contexts. Your expertise will be instrumental in creating a safer and more meaningful user experience on their journey to find an intimate connection.Responsibilities • Develop, deploy, and maintain end-to-end machine learning models to identify and mitigate bad actors, remove policy-violating content, and ensure user safety., • Design and implement scalable systems (e.g., using Spark, Kubernetes) to preprocess data, run inference, and manage post-processing pipelines., • Define standardized performance metrics, testing protocols, and evaluation processes to measure the effectiveness, identify and mitigate potential risks, and ensure fairness of AI solutions., • Ensure ongoing assessment and refinement of AI solutions, incorporating user feedback, business impact, and emerging ethical considerations., • Collaborate closely with Data Scientists, Data Engineers, Product Managers, Backend Engineers, and the AI Platform Team to ensure a comprehensive and coordinated approach to user safety., • Stay abreast of new trends and research in AI/ML that can be applied to Trust & Safety initiatives to improve detection, user safety, and stay ahead of potential threats.What We're Looking For, • Strong programming skills: Proficiency in languages like Python, Java or C++ and SQL, proficiency in at least one ML stack (e.g., PyTorch), and strong understanding of data pipelines, • Domain expertise: Deep understanding of machine learning, deep learning, and emerging AI technologies. Proven track record of building, debugging, and fine-tuning real-time machine learning models for user facing products. Experience with applying expertise to fraud detection, content moderation, or related fields is a plus ., • System design & architecture: Experience training and deploying large scale ML models. Good understanding of distributed computing for learning and inference., • Evaluation frameworks for LLMs: Experience designing robust testing protocols to ensure effectiveness, fairness, and safety of AI-driven features., • Cloud and data platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with solutions like Databricks, Ray, or KubeFlow is a plus., • Data engineering knowledge: Skills in handling and managing large datasets including, data cleaning, preprocessing, and storage. Good understanding of batch and streaming pipelines as well as orchestrators like Argo and Airflow., • Strategic technical leadership skills: Demonstrated track record of guiding teams through complex ML projects in alignment with product and business objectives., • Collaboration and communication skills: The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds., • Strong written communication: The ability to communicate complex ideas and technical knowledge through documentation. Prior Experience, • 4+ years of experience, depending on education, as an MLE or data scientist. Previous experience working in Trust & Safety or related fields (e.g., fraud detection, content moderation, compliance) is preferred., • 2+ years of experience in applying end-to-end machine learning models, including data collection, model training, deployment, and monitoring in an industry setting, • 1+ years of experience integrating LLMs in real-world applications with the appropriate baseline metrics and evaluation methodologies., • 1+ years of experience utilizing ML infrastructure components such as a feature store, model training environment, model serving environment, observability, workflow orchestrator, etc. #Hinge .

Job DescriptionRadical AI, Inc. is an artificial intelligence company that is accelerating scientific research & development. We are at the forefront of innovation in the field of materials R&D, a critical driver for advancing our most cutting-edge industries and shaping the future. Breaking away from the traditionally slow and costly R&D process, Radical AI leverages artificial intelligence and machine learning to pioneer generative materials science. This innovative field blends AI, engineering, and materials science, revolutionizing how materials are created and discovered. Radical AI's approach speeds up R&D and addresses global challenges, setting new benchmarks in technology and sustainability. The opportunityAs an AI Researcher specializing in generative models for materials discovery at Radical AI, you will help the development of the first commercial foundation model for materials science. Your role involves pioneering the application of generative models in the field of materials science, in particular by leveraging flow matching, diffusion, and LLMs. You will develop novel models and training techniques tailored for atomistic data in materials science. Your responsibilities include designing and conducting large-scale experiments to validate the most promising approaches in generative modeling. Collaborating closely with our engineering and computational materials science teams, you will play a crucial role in transitioning state-of-the-art models from research to production. Your expertise will contribute to the broader research community through publications in top-tier AI/ML venues like NeurIPS, ICML, and ICLR, alongside active participation in conferences and workshops. This role offers the unique opportunity to mentor and guide junior members of our technical team and research interns, fostering a culture of growth and innovation. Positions are available at various levels of seniority: Senior, Staff, and Principal.Mission • Lead and develop our generative foundation models in materials discovery., • Work in collaboration with various teams, in particular the quantum chemistry team, the atomistic simulation team, the engineering team, and the experimental team., • Conduct large-scale experiments to validate and refine promising approaches, collaborating closely with engineers to implement these models in production., • Develop rigorous benchmarks to validate and test the performance of our models., • Contribute to the AI and materials science research community through publications and active engagement in top-tier AI/ML venues like NeurIPS, ICML, ICLR, and our company blog, alongside active participation in conferences and workshops., • Tackle challenging problems with new and different ideas, creativity and contrarian thinking., • Mentor and guide junior team members and interns, promoting an environment of continuous learning and innovation.About you, • Ph.D., M.S., or B.S. in Computer Science, AI, Machine Learning, Applied Maths, or a closely related field, with a strong focus on deep learning and generative models., • At least 3 years of research experience in AI, with a proven track record in generative modeling, particularly in fields adjacent to materials science., • Working knowledge of various generative AI architectures, including transformers, diffusion models, CNFs, and flow matching., • Demonstrated experience in designing and running large-scale experiments in AI and machine learning., • Passionate about leveraging ML for science related problems and a commitment to doing world-class research., • Proficiency in Python and relevant ML libraries (e.g., PyTorch)., • Strong publication record in top-tier AI/ML conferences or journals., • Excellent collaboration and communication skills, capable of articulating complex technical ideas clearly and effectively.Pluses, • Prior experience in transitioning AI research into production environments., • Active involvement in the AI research community, with contributions beyond publications, such as organizing workshops or giving talks at conferences.What we offer, • A competitive compensation package also includes the best in benefits:, • Medical, dental, and vision insurance for you and your family, • Mental health and wellness support, • Unlimited PTO and 14+ company holidays per year, • 401K, • Work closely with a team on the cutting edge of AI research. Disclosure Radical AI is committed to equal employment opportunity regardless of race, color, ancestry, national origin, religion, sex, age, sexual orientation, gender identity and expression, marital status, disability, or veteran status.

Job DescriptionAbout CookUnity: Food has lost its soul to modern convenience. And with it, it has lost the power to nourish, inspire, and connect us. So in 2018, CookUnity was founded as the first-of-its-kind platform that connects the world with the source of truly great food: chefs. Today, CookUnity delivers 50 million meals a year from the industry's best chefs to homes all over the country. Fresh. Ready-to-eat. And crafted with the passion that nourishes body and soul. Unwilling to stop there, CookUnity is expanding beyond delivery to become an ever-innovating marketplace focused on our singular mission: empower Chefs to nourish the world. If that mission has you hungry in more ways than one, you've found the right job posting. The role: We're looking for a Senior Manager, Data Science/ML who will drive CookUnity's next phase of product innovation through forward-looking data science capabilities. This role goes beyond traditional analytics—you'll be responsible for building the ML and experimentation foundation that enables personalized, intelligent product experiences at scale. As Senior Manager, you'll own the strategic vision for how data science shapes our product roadmap. You'll build and lead a team focused on predictive modeling, personalization, experimentation frameworks, and emerging ML capabilities that directly impact customer engagement, retention, and lifetime value. This is a high-impact role for someone who thinks strategically about the future of product science while remaining hands-on in driving technical execution. Responsibilities:Strategic Vision & Product Partnership • Define and execute the product data science strategy, identifying opportunities where ML and predictive analytics can unlock step-change improvements in customer experience and business outcomes, • Partner closely with Product, Growth, Engineering, and UX leadership to influence product roadmap with data-driven insights and forward-looking ML capabilities, • Act as a thought leader on emerging data science techniques (personalization, recommendation systems, causal inference, generative AI) and their application to product problems, • Translate complex product challenges into clear data science problems with measurable success criteria, • Own the end-to-end ML lifecycle for product use cases: problem framing, feature development, model training, deployment, monitoring, and iteration, • Partner with the Growth Data Science & Analytics team to align experimentation, measurement, and modeling efforts into a cohesive end-to-end data science ecosystem.Team Leadership & Development, • Build, mentor, and scale a high-performing product data science team capable of delivering both strategic insights and production ML systems, • Foster a culture of innovation, experimentation, and continuous learning within the data science organization, • Create career development pathways that attract and retain top data science talent, • Collaborate with Analytics Engineering to ensure seamless model deployment and monitoringAdvanced Analytics & ML Capabilities, • Own and evolve personalization and recommendation systems that drive engagement and conversion across the customer journey, • Design and implement robust experimentation frameworks that enable rapid, high-quality product testing and learning, • Develop causal inference methodologies to understand true incrementality of product changes., • Ensure models are observable, explainable where needed, and continuously improved post-launchProduct Measurement & Impact, • Define product success metrics and measurement frameworks that align with business objectives, • Build scalable dashboards and monitoring systems that provide real-time visibility into product performance, • Conduct deep-dive analyses on user behavior patterns to uncover opportunities for product optimizationQualifications:, • 8+ years of experience in data science, with at least 3 years in leadership roles managing data scientists or ML engineers, • Proven track record building and deploying ML models in production, particularly in personalization, recommendation systems, or predictive modeling, • Deep expertise in experimentation and causal inference, including A/B testing, incrementality measurement, and statistical rigor, • Strong product sense and business acumen—ability to identify high-impact opportunities and translate them into data science initiatives, • Experience in consumer tech, e-commerce, or marketplace businesses where personalization and user engagement are critical, • Excellent communication skills—ability to explain complex technical concepts to non-technical stakeholders and influence product strategy, • Hands-on technical proficiency in Python, SQL, and modern ML frameworks (scikit-learn, PyTorch, TensorFlow), • Experience with cloud-based data infrastructure (AWS, GCP, Snowflake) and ML Ops tools (MLflow, Airflow, Kubeflow)Preferred requirements:, • PhD or Master's degree in Computer Science, Statistics, Mathematics, or related quantitative field, • Experience with real-time ML systems and feature stores, • Background in recommendation systems or two-tower/multi-modal embeddings, • Familiarity with generative AI and LLM applications in product contexts, • Experience building data science teams from scratch or through periods of rapid growth, • Prior work in subscription businesses or retention-focused products, • Knowledge of modern product analytics tools (Amplitude, MixPanel, Looker)What Success Looks Like, • 6 months: Established product data science roadmap aligned with business priorities; shipped at least one high-impact ML model to production; built strong partnerships with Product and Engineering leadership We hope this provides valuable insight into our culture and product vision. If this excites you, we'd love to connect! Benefits 🩺 Health Insurance coverage 🌅 401k Plan 📈 We grow, you grow: Stock Options Plan granted on Day 1 🌟 Eligible for a bi-annual performance bonus ⛱ Unlimited PTO 🗓️ 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical 🐣 Paid Family leave 🕯 Compassionate Leave: 3-5 days each time the need arises 🥘 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly 🧘🏽️‍♀️ Wellness perks: access to fitness subsidies to build a healthy lifestyle 👩🏾️‍🏫 Personalized Spanish coach 🚀 Awesome opportunity to join a company that is looking to change how we eat and how chefs work! Compensation All final pay rates will be determined by candidates experience, knowledge, skills, and abilities of the applicant, internal equity, and alignment with market data.Pay Range for this position$225,000—$240,000 USD If you're interested in this role, please submit your application, and if we think you might be a fit, we'll get in touch with you. Thank you for your time! CookUnity is an Equal Opportunity Employer. We are dedicated to creating a community of inclusion and an environment free from discrimination or harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity, national origin, citizenship status, protected veteran status, genetic information, or physical or mental disability. A quick note for all candidates We've recently seen an increase in recruitment scams across the industry, and we want to make sure you (and your data) stay safe while applying to CookUnity. We also want you to know that we take this seriously — sometimes, as part of our process, we may ask for a brief "proof of humanity" to confirm that we're connecting with a real person, not an impersonator. Here are a few tips to help you protect yourself and know what to expect from us: • Apply only through our official channels. All open roles are listed on our official careers page: careers.cookunity.com, • Our recruiters are real people — and easy to verify. You can always find them on LinkedIn with verified profiles. If you're unsure, feel free to reach out to us on our official LinkedIn Company Page., • We only communicate through official CookUnity channels. That means emails ending in @cookunity.com and interviews held through official company platforms (Google Meet or Zoom) — never WhatsApp, Telegram, or SMS.

Job Description Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales — from molecules to organisms — enabling us to predict, understand, and program living systems in ways never before possible. Output Biosciences is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI and biology, and backed by top VCs including Y Combinator. As a Generative AI Research Scientist, you'll work alongside our founders and team members to develop advanced generative models that can synthesize and design biological systems at multiple scales. Building upon our biological reasoning model, you'll focus on creating the generative capabilities that turn insights into innovations. * ⁠You will design and develop cutting-edge generative models specifically for biological data, creating AI systems that can generate novel molecular structures, protein designs, cellular components, and biological pathways. * You will design and implement state-of-the-art generative algorithms including diffusion models, language diffusion models, diffusion transformers, and flow matching approaches and tailor them to biological constraints and properties * You will train and scale innovative AI models using large, diverse biological multi-modal datasets across distributed GPU clusters. * You will solve challenging AI research problems at scale, tackling key aspects such as model architecture and scaling, pre-training and fine-tuning strategies, and rigorous evaluation methods. * Your work will span various advanced generative AI architectures, including transformers, diffusion models, and autoencoders, exploring and implementing these techniques to push the boundaries of biological AI. Who We're Looking For: * You have a Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Physics, or a relevant technical field. * You have a PhD with 2 years of research experience, or a Bachelor's degree with 4+ years of research or industry experience in Deep Learning, Artificial Intelligence, or other relevant fields. * You have a strong publication record in top-tier AI conferences or journals (e.g., NeurIPS, ICML, ICLR). * You have extensive hands-on experience building and training generative models, such as diffusion models, GANs, VAEs, normalizing flows, or autoregressive models. * You are proficient in Python and have expertise in at least one major deep learning framework (PyTorch, TensorFlow, or JAX). Who You Are: * You have excellent problem-solving skills and the ability to quickly adapt to new challenges. * You exhibit a proactive approach to problem-solving, thinking beyond the specific task, taking ownership of challenges, and taking pride in solving them. * You have a mature mindset in ambiguous situations, helping to frame questions and seek clarity while making decisions in the face of uncertainty. * You have excellent communication skills and can clearly articulate complex technical concepts. * You are motivated by making a real impact and are committed to tackling problems of significant consequence with determination and creativity. Bonus points: * You have experience applying machine learning to biological or chemical problems. * You have knowledge of physics, molecular biology, chemistry, computational biology, bioinformatics, cheminformatics or related fields. * You have experience with multi-modal learning. * You have contributed to open-source machine learning projects. * You have experience in developing efficient code in C/C++. Our Values ❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions. 🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards. 🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community. 📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner. 🎮 Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling. What We Offer * We encourage new and different ideas, creativity and contrarian thinking * Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you * You own your day-to-day management. What we care about is that we all hit our milestones * Competitive salary and equity in a growing, well-funded startup * Excellent medical, dental, and vision coverage Compensation Range: $120K - $250K

Job Description Mirage is an AI-native video platform that intelligently orchestrates production and editing through natural language. Our models leverage contextual awareness to execute the same creative decisions a professional editor would — dramatically improving productivity for experienced teams, while making video creation accessible to anyone. We’re an interdisciplinary team addressing some of the most difficult technical and creative challenges in generative media. As an early member of our team, you’ll tackle foundational problems that remain largely unsolved across the industry, driving an outsized impact on the future of creative expression. More about us Product (Captions by Mirage) Research (Seeing Voices, technical-white-paper) Updates (Mirage on X / twitter) TechCrunch, Forbes AI 50, Fast Company (press) Our Investors We’re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, General Catalyst, Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more. Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square) About the Role Mirage is seeking a Research Engineer to build and scale the systems powering our video generation models. You’ll work closely with researchers to optimize performance, improve efficiency, and bring cutting-edge models into production. This role sits at the intersection of research and systems engineering, focusing on making advanced models faster, more efficient, and capable of ultra-low latency, real-time generation. Responsibilities * Train and optimize large-scale video and multimodal models * Improve efficiency across training and inference (memory, latency, cost) * Implement techniques such as distillation, quantization, and pruning to aggressively accelerate diffusion and autoregressive generation * Build and maintain distributed training systems * Optimize GPU utilization, parallelism, and throughput * Develop tooling for experimentation, evaluation, and debugging * Translate research models into robust, production-ready systems * Monitor and improve model performance in real-world usage What makes you a great fit * 2+ years of professional industry experience * Strong experience in deep learning systems and infrastructure * Expertise in PyTorch, CUDA, Triton, and distributed training (FSDP, etc.) * Experience scaling and optimizing large models under low-latency inference constraints * Strong debugging and performance profiling skills * Ability to move quickly from prototype to production * Strong software engineering fundamentals Benefits: * Comprehensive medical, dental, and vision plans * 401K with employer match * Commuter Benefits * Catered lunch multiple days per week * Dinner stipend every night if you're working late and want a bite! * Grubhub subscription * Health & Wellness Perks * Multiple team offsites per year with team events every month * Generous PTO policy Captions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please note benefits apply to full time employees only. Compensation Range: $175K - $275K

Job DescriptionResearch Intern (PhD), Machine Learning Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales — from molecules to organisms — enabling us to predict, understand, and program living systems in ways never before possible. Output Biosciences is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI and biology, and backed by top VCs including Y Combinator. Our internships offer flexible commitment, with a minimum of 20 hours per week, ranging 12 to 24 weeks. We have various start dates available to accommodate your academic schedule. There may be opportunities for full-time employment upon successful completion of your PhD. * You will contribute to the development of novel machine learning approaches for biological data analysis and interpretation * You will design and implement experiments to evaluate and improve AI models using large-scale biological datasets * You will collaborate with our interdisciplinary team to tackle complex challenges in molecular biology and drug discovery * You will present your research findings and contribute to publications in top-tier conferences and journals * You will have the opportunity to work on projects that directly impact the future of medicine and biotechnology Who We're Looking For * You are currently pursuing a PhD in Machine Learning, Computer Science, Computational Biology, or a related field * You have a strong background in deep learning, with experience in frameworks such as PyTorch or TensorFlow * You have a proven track record of research, demonstrated by publications at conferences such as NeurIPS, ICML, ICLR, or relevant computational biology venues * You are proficient in Python and have experience with large-scale data processing and analysis * You have excellent problem-solving skills and the ability to work independently on complex research problems * You are passionate about applying AI to solve real-world challenges in biology and medicine * You have strong communication skills and can effectively present technical concepts to diverse audiences * You thrive in a fast-paced, startup environment and are excited about making a significant impact in a growing field Bonus Points * Experience with biological data analysis or computational biology projects * Familiarity with generative AI models, such as transformers or diffusion models * Contributions to open-source machine learning or bioinformatics projects Our Values ❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions. 🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards. 🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community. 📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner. 🎮 Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling. What We Offer * We encourage new and different ideas, creativity and contrarian thinking * Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you * You own your day-to-day management. What we care about is that we all hit our milestones * Competitive salary and equity in a growing, well-funded startup * Excellent medical, dental, and vision coverage

Job DescriptionDescription: About Us At Biz2Credit, we look for individuals who are ready to join a dynamic and innovative fintech company on a mission to change the lending landscape for small businesses. Our values of Collaboration, Responsibility, Empowerment, Disruption, Innovation, and Trust guide everything we do, and our purpose of helping small businesses succeed drives us forward. As a company, we believe that with the right tools and support, small business owners can achieve their dreams, and we're here to make that happen. That's why we're dedicated to developing cutting-edge solutions, like our Biz2X platform, a fully configurable SaaS solution that leverages artificial intelligence and machine learning to make lending more efficient, effective, and accessible. But we're more than just another FinTech company. We're a team of individuals who bring their unique personalities, backgrounds, and experiences to work every day. We believe that diversity makes us stronger, and that's why we value a culture that is inclusive and supportive. We're looking for people who are excited about the opportunity to make a difference, who want to work in an environment that is both challenging and fun, and who are eager to bring their whole selves to work. So if you're someone who is eager to join a company that is making a real impact, who values a positive and inclusive workplace culture, and who is ready to be a part of a team that is changing the lending landscape, we want to hear from you. Come join us and be a part of something truly special at Biz2Credit. About the Role This is a rare opportunity to join a fast-growing team, where you will play a major role in shaping Biz2X's future. We're looking for an exceptional candidate who is excited about the opportunity to build a next-generation financial services business. We believe that there is a tremendous opportunity to leverage cutting-edge data science to inform smarter, faster decision-making. As a Biz2Credit leader in data science, you will shape the company's data-centric culture, work closely with our engineering team to develop our analytics infrastructure, and collaborate closely with our Chief Risk Officer on developing, validating, and automating our customer conversion and underwriting models. Hands-on credit risk/modelling experience in a consumer/small business lending financial institute is a must. Responsibilities Team Leadership and Management • Lead, mentor, and develop a team of data scientists, providing guidance and support in their professional growth and career advancement., • Foster a collaborative and inclusive team culture that encourages creativity, critical thinking, and continuous learning., • Collaborate with product, marketing, and engineering teams to analyze and optimize the application funnel, leveraging data-driven insights to enhance user acquisition, conversion rates, and retention., • Utilize predictive modelling and machine learning techniques to identify factors influencing user behavior throughout the application process, enabling targeted interventions to improve user experience and maximize conversion rates., • Implement A/B testing methodologies and experimentation frameworks to iteratively refine and optimize the application funnel, driving continuous improvement in key performance metrics such as conversion rates, customer lifetime value, and user engagement., • Monitor and analyze key metrics related to the application funnel, such as click-through rates, bounce rates, drop-off points, and conversion funnels, to identify areas for improvement and develop data-driven strategies to address them., • Collaborate with cross-functional teams to implement data-driven solutions, such as personalized user experiences, dynamic content optimization, and predictive lead scoring, to streamline the application process and enhance user engagement at each stage of the funnel., • Lead the development and maintenance of credit risk models, leveraging advanced statistical techniques and machine learning algorithms to assess and mitigate credit risk across various financial products and customer segments., • Collaborate with risk management and credit underwriting teams to define model requirements, gather relevant data sources, and validate model performance against established benchmarks and regulatory requirements., • Incorporate both traditional and alternative data sources, such as transactional data, behavioral data, and alternative credit data, to enhance the predictive power and robustness of credit risk models., • Monitor the performance of credit models over time, conducting regular model reviews, back testing, and sensitivity analyses to ensure accuracy, stability, and alignment with business objectives., • Work closely with cross-functional teams to implement credit models into decision-making processes, such as loan origination, credit scoring, and portfolio management, and provide ongoing support and guidance to ensure effective model deployment and utilization., • Collaborate with cross-functional teams to define and implement data strategies that support business goals and drive innovation in the lending domain., • Lead the design, development, and deployment of advanced analytics models and machine learning algorithms to extract actionable insights from large, complex datasets., • Partner with product managers and engineers to integrate data science solutions into existing products and platforms, as well as to conceptualize and develop new data-driven products and features., • Collaborate closely with key stakeholders, including executives, business leaders, and external partners, to understand business requirements, communicate insights, and influence decision-making., • Present findings, recommendations, and project updates clearly and compellingly through visualizations, reports, and presentations. Requirements: • Master's or Ph.D. degree in Computer Science, Statistics, Mathematics, Economics, or a related field., • 8+ years of experience in data science, machine learning, or artificial intelligence roles, preferably in the Lending or financial services industry., • 3+ years of experience in a leadership or management position, with a proven track record of successfully leading and developing high-performing teams., • Proficiency in programming languages such as Python, as well as in data manipulation and analysis tools (e.g., Pandas, NumPy, scikit-learn)., • Strong understanding of statistical methods, machine learning algorithms, and data visualization techniques., • Expertise in NLP techniques and text analytics., • Familiarity with neural network architectures and deep learning frameworks (Pytorch), • Experience with big data technologies and platforms (e.g. AWS) is highly desirable., • Excellent communication skills, with the ability to translate complex technical concepts into business insights and recommendations., • Demonstrated ability to drive innovation, influence stakeholders, and deliver results in a fast-paced, dynamic environment.

Job DescriptionHinge is the dating app designed to be deleted In today's digital world, finding genuine relationships is tougher than ever. At Hinge, we’re on a mission to inspire intimate connection to create a less lonely world. We’re obsessed with understanding our users’ behaviors to help them find love, and our success is defined by one simple metric– setting up great dates. With millions of users across the globe, we’ve become the most trusted way to find a relationship, for all. About the Role: We are hiring a Staff Machine Learning Engineer to drive the design, development, and deployment of machine learning systems that power our core products in User Growth and Monetization. You will work on building deeply personalized user experiences that drive business growth and meet individual needs and preferences: by targeting the right users with the right products at the right time, we empower product teams to drive meaningful growth in revenue and user engagement while enhancing user satisfaction. The Growth Product Group is responsible for the development of paid features to accelerate dating outcomes, driving engagement throughout a user’s lifecycle and making Hinge the dating destination for all communities. You can expect to work on a broad range of problems, from identifying how to send the right message to the right user at the right time to optimizing the efficacy of our paid offerings. This is a fast growing team, and you will help define the vision and strategy that drives meaningful growth and accelerates machine learning at Hinge.Responsibilities: • Lead the end-to-end development of production-grade ML systems such as user targeting models that will help drive engagement, improve dating outcomes and/or improve user adoption of and engagement with paid features, • Define and own the technical roadmap for ML within your product area and align with company-wide priorities, • Collaborate closely with ML Engineers, Data Scientists, and Product Managers to understand their needs and identify opportunities to accelerate the AI/ML development and deployment process, • Design, advocate, and implement for availability, scalability, operational excellence, and cost management while delivering impact to our daters incrementally, • Keep abreast of and bring to Hinge applicable cutting-edge research, technologies, and best practices in the ML/AI space., • Mentor and educate ML Engineers on current and up and coming research, technologies and best practices of doing ML at scale., • Ensure the ethical and responsible use of ML/AI and compliance with privacy regulations to protect user data, • Communicate effectively to audiences of various technical and non-technical backgroundsWhat We're Looking For:, • Strong programming skills: Proficiency in Python and ML libraries such as PyTorch, • Domain expertise: Deep understanding of machine learning, deep learning, and emerging AI technologies. Proven track record of building, debugging, and fine-tuning machine learning for user facing products. Experience with causal inference, uplift modeling, and interventional data collection is a plus., • System design & architecture: Strong background in setting up and optimizing ML infrastructure, including containerization (Docker), orchestration (Kubernetes), and CI/CD workflows for ML (e.g., model versioning, automated testing)., • Cloud platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with ML serving solutions like Ray, KubeFlow, or Weights & Biases is a plus., • Data engineering knowledge: Skills in handling and managing large datasets including data cleaning, preprocessing, and storage. Good understanding of batch and streaming pipelines as well as orchestrators like Argo and Airflow., • Collaboration and communication skills: The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds.., • Software leadership skills: A track record of leading projects through completion with quantifiable and measurable outcomes., • 5+ years of experience, depending on education, as an MLE, with at least 2 years in a senior or staff-level role, • Previous experience in User Growth or Monetization, • 3+ years of experience designing and developing end-to-end, production grade ML systems, • 4+ years of experience working in a cloud environment such as GCP, AWS, Azure, • 3+ years of experience leading projects with at least 1 other team member through completion. #Hinge .

Job Description Do you want to be part of the core team that is building the next one-of-a-kind tech companies that can potentially change your career's trajectory?! We are striving to build the future of AI for consumer enterprises, and our founders need your help as we are growing. Come join us and leave your mark! Our founders are looking for a highly ambitious and highly technical Head of Technology to lead the strategy, development, and integration of AI systems across all layers of the AI stack. This senior executive role requires deep technical expertise in both AI/ML and full-stack development, combined with strong leadership, strategic vision, and business acumen. They are familiar with startup environments and bridge the gap between technical teams and business stakeholders to drive innovation and deliver robust, scalable, and ethical AI-powered products. RESPONSIBILITIES • Hands-on Technical Implementation, Architecting, and Oversight, • Design and implement end-to-end systems: Guide and implement the AI-Native platform of Verneek, as well as its solution suite, fullstack: from backend infrastructure to data ingestion, model training and inference, to front-end interfaces and applications., • Architect scalable solutions: Ensure the development of robust, scalable, secure, and maintainable full-stack systems that can deploy and run AI models in production at scale., • Evaluate and select technology: Assess and recommend the use of appropriate AI frameworks (e.g., PyTorch, TensorFlow), cloud platforms (e.g., AWS, Azure), and other tools and vendors., • Enforce best practices: Drive and enforce coding standards, technical architecture patterns (e.g., microservices), and quality control mechanisms., • Strategic leadership and overall vision, • Define and execute the technology strategy: Set the vision, roadmap, and strategic priorities for how Verneek’s fullstack technologies will create business value, improve products, and drive operational efficiency., • Align with business objectives: Collaborate with senior leadership and product teams to translate business needs into technical specifications and viable AI solutions., • Team leadership and management, • Manage projects: Oversee project planning, resource allocation, and budget management to ensure successful, on-time, and high-quality delivery., • Build and mentor teams: Recruit, develop, and manage high-performing teams of Software/AI/ML engineers, full-stack developers, and MLOps specialists, and beyond., • Foster a culture of innovation while delivering quickly: Encourage experimentation, continuous learning, and adaptability to emerging technologies and trends. Requirements • Advanced hands-on technical expertise: Demonstrated hands-on expertise in both AI/ML engineering (including LLMs, computer vision, NLP, etc.) and modern full-stack development as an individual contributor., • Experience with cloud and MLOps: Proficiency with cloud environments (AWS, GCP, Azure) and scaling MLOps for model training, deployment, inference, and monitoring., • Leadership experience: Proven track record of leading and managing engineering or AI/ML teams., • Strategic thinking: Ability to develop a long-term technical vision and align it with overall product and business strategy., • Excellent internal and external communication: The ability to communicate complex technical concepts to both technical and non-technical audiences, including executive leadership and Verneek partners., • Startup Experience:. Prior track record of having helped built series of technologies at a deeply technical startup. MINIMUM QUALIFICATIONS • Bachelor’s Degree in CS/CE/AI other technical fields, • Work authorization in the USA at the time of hire At Verneek, we are very determined to build a company that promotes diversity of thought that comes from the diversity of the individuals on the team! Candidates from any gender identity, race, color, religion, sexual orientation, national origin, veteran, or disability status are highly encouraged to apply. Benefits Stellar medical, dental, vision, disability, and life insurance Daily private Chef lunch, curated to personal diets Transportation Benefits 401K matching contributions Flexible PTO Visa/Green Card Sponsorship Career growth support through sponsoring learning opportunities and mentorship About Verneek Verneek is an early-stage deep-tech AI startup, based in the NYC area, founded by a team of leading AI research scientists and backed by a group of world-renowned business and scientific luminaries. Our mission is to build the most helpful AI for anyone, anywhere, at anytime. We are obsessed with what we do and we have fun doing it. Read more about verneek here: and make sure to watch all our introductory videos and yearly recaps here: . Verneek Culture It’s often hard to put “culture” into words, perhaps you can get a visual sense of our culture here: . We all obsessively love what we do, care about each other, share all sorts of meals together, celebrate all kinds of events together, and work tirelessly with the excitement of making a difference through AI innovation. We are enjoying the journey, and going through all the ups and downs together. Although we have come a very long way in setting the foundations of our unique company, but we still have ways to go and you can help shape our culture! The core Verneek team plays a crucial role in further shaping the culture of the company moving forward. We are looking for highly ambitious and tremendously driven individuals who can take the lead in driving various aspects of the company, and help us shape its lasting impact. Annual Salary Range: [tbd]

Job Description Tagup is a defense technology company founded at MIT that is delivering logistics decision advantage with next-generation AI. We’re growing rapidly and are looking for change-makers passionate about delivering innovative technologies to solve the most challenging problems in the world’s highest stakes environments. This is an exciting opportunity to engage in meaningful work that strengthens national security and contributes to the success of U.S. and allied forces. Join us in shaping the future of defense logistics for a safer tomorrow. We are seeking a Machine Learning Engineer to join our Salt Lake City team and help shape the next generation of AI-driven defense and aviation systems. In this role, you’ll go beyond building models — you’ll design, deploy, and scale AI solutions that directly support mission-critical operations. This is not a typical ML position. You’ll work at the intersection of cutting-edge research and real-world application, creating models and infrastructure that deliver measurable improvements in reliability, efficiency, and performance. If you’re motivated by solving complex technical challenges and want your work to make a tangible impact on national security and aviation safety, we want to hear from you.What You’ll Do • Develop, train, and optimize ML models for large-scale applications., • Build pipelines for data ingestion and model deployment., • Work with engineers and subject-matter experts to refine solutions., • Conduct testing and validation to ensure reliability., • Co-author technical reports on data analysis and model performance., • Continuously improve ML infrastructure and workflows., • Collaborate with customers to identify new data sources and the industrial processes they will support; some customer travel may be required.What We’re Looking For, • 4+ years of machine learning experience, with strong Python skills and proficiency in frameworks such as PyTorch or TensorFlow., • Proven ability to deploy ML models into production and work with large, complex datasets., • Hands-on experience with MLOps tools and practices, including Kubernetes, MLflow, and CI/CD pipelines., • Experience building and managing cloud infrastructure as code (AWS, Azure, or GCP) with tools such as Terraform or Ansible. Tagup is an equal opportunity employer and individuals seeking employment with us are considered without regard to race, color, religion, national origin, age, sex, marital status, physical or mental disability, veteran status, gender identity, sexual orientation, or any other characteristic protected by law. Citizenship: Due to the nature of our work with the U.S. Department of Defense, applicants must be authorized to work for any employer in the U.S. We are unable to sponsor visas at this time. 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 DescriptionRadical AI, Inc. is an artificial intelligence company that is accelerating scientific research & development. We are at the forefront of innovation in the field of materials R&D, a critical driver for advancing our most cutting-edge industries and shaping the future. Breaking away from the traditionally slow and costly R&D process, Radical AI leverages artificial intelligence and machine learning to pioneer generative materials science. This innovative field blends AI, engineering, and materials science, revolutionizing how materials are created and discovered. Radical AI's approach speeds up R&D and addresses global challenges, setting new benchmarks in technology and sustainability. The opportunityThe vision for this opportunity is to create an intelligent system that operates in an experimental material science setting. Your core responsibility will be to lead the development of an agentic system for materials development, enhancing reasoning and planning throughout the development process, encompassing data acquisition, model evaluation, pre- and post-training, supervised fine-tuning, reward modeling, and reinforcement learning to drive overall performance of the system. Your expertise will contribute to the broader research community through publications in top-tier AI/ML venues like NeurIPS, ICML, and ICLR, alongside active participation in conferences and workshops. This role offers the unique opportunity to mentor and guide junior members of our technical team and research interns, fostering a culture of growth and innovation. Positions are available at various levels of seniority: Senior, Staff, and Principal.Mission • Drive the development of a system that can pursue complex, multi-objective goals in materials design with limited direct supervision, leveraging agents and multi-agents that can interact with third-party and in-house integrations, including APIs, code interpreters, and hardware components., • Leverage various LLM architectures and models to balance reasoning and continuous adaptation towards intelligent decision-making., • Synthesize large-scale, high-quality (multi-modal) data through methods such as rewriting, augmentation, and generation to improve the abilities of models in various stages., • Work in collaboration with various teams, in particular the experimental materials science team., • Develop and apply reliable evaluation methods to analyze model performance at different stages, uncover the mechanisms and origins of their capabilities, and leverage these insights to enhance model development., • Contribute to the AI and materials science research community through publications and active engagement in top-tier AI/ML venues like NeurIPS, ICML, ICLR, and our company blog, alongside active participation in conferences and workshops., • The ability to tackle challenging problems with new and different ideas, creativity and contrarian thinking., • Mentor and guide junior team members and interns, promoting an environment of continuous learning and innovation.About you, • Ph.D., M.S., or B.S. in Computer Science, AI, Machine Learning, Applied Maths, or a closely related field, with a strong focus on LLMs., • At least 3 years of research experience in AI, with a proven track record of designing agentic systems., • Familiarity with large-scale model training., • Proficiency in Python and relevant ML libraries (e.g., PyTorch)., • Strong publication record in top-tier AI/ML conferences or journals., • Excellent collaboration and communication skills, capable of articulating complex technical ideas clearly and effectively.Pluses, • Passionate about leveraging ML for science related problems and a commitment to doing world-class research., • Domain knowledge of materials and/or molecules., • Familiarity with large-scale model training., • Experience with LLM engineering., • Active involvement in the AI research community, with contributions beyond publications, such as organizing workshops or giving talks at conferences.What we offer, • A competitive compensation package also includes the best in benefits:, • Medical, dental, and vision insurance for you and your family, • Mental health and wellness support, • Unlimited PTO and 14+ company holidays per year, • 401K, • Work closely with a team on the cutting edge of AI research. Disclosure Radical AI is committed to equal employment opportunity regardless of race, color, ancestry, national origin, religion, sex, age, sexual orientation, gender identity and expression, marital status, disability, or veteran status.

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 You'll Do: A lab signs with CoreWeave. They have thousands of GPUs waiting. Their first month? Spent on cluster setup instead of research. Building deployment scripts, fighting container images, wiring up job orchestration. They came to train models. Instead, they're doing operations. This is the problem. We're building the Applied Training team to fix it. You'll be an early member of a small team, responsible for our Kubernetes-native research cluster platform, or the sandbox client for agentic training and evaluation, or possibly a new project altogether. The goal is specific: Give every CoreWeave customer the research infrastructure that currently only exists inside frontier labs. About the role: • Contribute to the roadmap for Applied Training. Figure out what actually unlocks new workloads and what's just nice to have. Work directly and closely with customers, and other teams inside of CoreWeave that are building cloud native primitives. Compute, storage, networking, etc., • For the research cluster platform: design and build a complete research cluster experience. CLI, job configuration schema, Kubernetes operators, daemons. Solve the problems researchers actually hit: code distribution, checkpoint-triggered evaluation, cross-cluster scheduling, programmatic job control. Replace the patchwork of scripts customers keep building on their own., • For sandbox infrastructure: own the Python SDK and work in a very tight loop with the backend team. When an RL training run needs to spawn thousands of isolated containers for agent rollouts, that's this system. When someone wants to run agent benchmarks at scale, that's this system. Make it work with our Kubernetes clusters, storage, and auth so researchers don't have to think about infrastructure., • Write the documentation for running popular OSS training frameworks on CoreWeave. The work that can unblock customers and help them succeed., • Work with infrastructure teams and customers directly. The customers are large AI labs running thousands of GPUs. Understand how they structure their internal supercomputing stacks. Bring that knowledge back to what we build.Who You Are:, • 5-8+ years building distributed systems, ML infrastructure, or developer platforms., • Real Kubernetes experience: custom controllers, operators, scheduling, CRDs, workload orchestration at scale. Not just deploying things to Kubernetes or cluster administration., • Excited about rigorous engineering, but enabled by AI based workflows., • You understand what makes researchers productive. Code distribution matters. Fast iteration cycles matter. Workflows that don't require becoming infrastructure experts matter., • Familiarity with training: how distributed jobs get scheduled, how ranks initialize, what breaks at scale., • You've shipped infrastructure that other people rely on daily. Not prototypes. Production systems., • Experience building internal ML platforms or research clusters at a company doing large-scale training., • Familiarity with agentic AI: RL training with rollouts, agent evaluation, sandbox isolation for running untrusted code., • Background with Slurm, Ray, or similar workload orchestration. Opinions on where they fall short., • Experience with container runtimes, isolation (gVisor, Kata), or serverless platforms., • 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 DescriptionCareer Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus equity.We are the leading virtual staining company revolutionizing digital pathology adoption worldwide through cutting-edge AI-powered technology. Our solutions deliver diagnostic-quality results in minutes while preserving tissue samples for comprehensive analysis. Our breakthrough DeepStain™ and ReStain™ technologies enable unlimited virtual staining from a single tissue sample, eliminating the bottlenecks and limitations of traditional chemical staining processes. This innovation supports the critical evolution from research applications to clinical deployment, empowering laboratories to advance their digital pathology capabilities while reducing chemical waste, improving operational efficiency, and expanding diagnostic possibilities. About the Role We are seeking an experienced Senior ML Engineer to join our team who owns the representation-learning and generative modeling stack that powers Pictor’s virtual staining. The ideal candidate will have deep expertise in Machine Learning and building generalizable, production-ready models, and evaluations that stand up in clinical workflows. Design and implement novel computer vision and deep learning algorithms for virtual staining and digital pathology applications Conduct rigorous experiments to evaluate algorithm performance, validate research hypotheses, and drive iterative improvements Develop and advance ML models leveraging Vision Transformers, Diffusion Models, GANs, and generative architectures for image-to-image translation tasks Apply classical and learned image enhancement, denoising, and semantic segmentation techniques to histopathology imaging challenges Explore image representation in latent space for efficient, high-fidelity virtual staining Stay current with state-of-the-art research, identifying opportunities to apply novel techniques to PictorLabs’ product roadmap Collaboration Collaborate with ML Engineering and software teams to translate research prototypes into production-ready systems meeting latency and throughput requirements Work with large-scale pathology datasets to train, validate, and fine-tune foundation models and custom architectures Partner with software engineers, data scientists, and pathology domain experts to integrate research into production systems Contribute to best practices for data engineering, data governance, and data quality across research and production pipelines Leverage AI coding and ideation tools to accelerate research velocity and prototype new approaches Required Qualifications PhD (preferred) or Master’s degree in Computer Science, Electrical Engineering, or a related field Deep expertise in computer vision and deep learning, with hands-on experience in one or more of: Vision Transformers, Diffusion Models, GANs, semantic segmentation, or classical image enhancement and denoising Expert proficiency in Python and PyTorch and other scientific computing environments a plus Strong mathematical foundation in linear algebra, probability, and optimization Experience with large-scale model training, distributed computing, or cloud ML infrastructure (AWS, GCP, or Azure) Knowledge of handling large scale image data, data version controls, model registry, has experience dealing with ML lifecycles Experience with feature search, data balancing, and data curation pipelines. Knowledge of software engineering best practices including version control (Git) and CI/CD pipelines Excellent collaboration and communication skills, with the ability to work effectively in a fast-paced, cross-functional international startup environment Extensive use of AI tools for coding, optimization, and ideation Preferred Qualifications Experience with medical imaging, digital pathology, or whole slide image (WSI) processing Experience with LoRAs, transformer architecture and state of the art image to image translation models (Flux 2, Z-Image) and the Hugging face ecosystem Background in generative models and fine-tuning of foundation models Experience with GPU acceleration and optimization, including CUDA kernel engineering, TensorRT/ONNX export, and inference serving frameworks such as Triton Experience with hosting computer vision model inference on NVIDIA DGX Spark. Understanding of FDA regulatory requirements for AI/ML in medical devices Experience with MLOps tools (MLflow, Kubeflow) and model versioning practices Develop tools and frameworks to streamline ML research workflows, experimentation, and reproducibility What We Offer The opportunity to work on technology that directly improves patient outcomes and transforms clinical diagnostics, alongside a talented team of engineers and researchers pushing the boundaries of AI in healthcare. You will have the freedom to pursue high-impact research while seeing your work deployed at scale in real clinical environments.

Job Description Senior Data Engineer – Cloud & AI Platforms Location: US / Canada (Remote/Hybrid) Type: Contract / Full-Time Overview: We are hiring a Senior Data Engineer to support large-scale data modernization and AI-driven transformation programs. This role focuses on building robust, scalable cloud data platforms and enabling advanced analytics and AI use cases. Key Responsibilities: • Architect and develop scalable data pipelines and cloud-native data solutions, • Collaborate with data scientists, analysts, and business stakeholders, • Strong experience in data engineering and cloud-based architectures, • Hands-on expertise with platforms like Databricks, Snowflake, Azure Synapse, or BigQuery, • Experience with ML/AI pipelines (Python, PyTorch, MLOps), • Exposure to GenAI frameworks such as LangChain or agent-based systems

Job Description Job Description: Palantir Data Engineer We are seeking a seasoned Data Engineer with 3-7 years of experience in data engineering, cloud platforms and distributed systems, along with 2+ years of hands-on experience with Palantir Foundry/ AIP. The ideal candidate will work on designing scalable data solutions, building robust data pipelines, modelling enterprise datasets and enabling analytics and AI/ML use cases on Palantir Foundry. Experience in the insurance domain is a plus. Location – Jersey City, NJ Key Requirements • 3-7 years of overall experience in data engineering, building and maintaining large-scale data pipelines and platforms., • 2+ years of hands-on experience with Palantir Foundry, including data ingestion, pipeline builder, transformations and working with Foundry datasets and applications., • Experience building interactive applications using Foundry Workshop, Slate and custom frontends using TypeScript., • Proficiency in programming languages such as Python, PySpark, and TypeScript/JavaScript., • Strong experience with AWS services for data processing and storage (e.g., S3, Glue, Athena, Lambda, Redshift)., • Deep understanding of microservices architecture and distributed systems., • Familiarity with AI/ML tools and frameworks (e.g., TensorFlow, PyTorch) and their integration into data pipelines., • Experience with big data technologies like Snowflake., • Strong problem-solving and performance optimization skills., • Exposure to modern DevOps practices, including CI/CD pipelines and container orchestration tools like Docker and Kubernetes., • Experience working in agile environments delivering complex data engineering solutions., • Palantir Foundry certification or demonstrated project experience is highly preferred., • 3+ years of work experience with Data Engineering, • 2+ years of work experience with Palantir, • 3+ years of work experience with Python (Programming Language)

Job DescriptionQuantitative Software Engineer | Intelligent Systems & Architecture Location: New York Metropolitan Area (Stealth) Total Compensation: $400,000 – $850,000+ (Aggressive performance-based upside) The Firm We are a premier, research-driven investment firm operating at the intersection of extreme-scale computing and mathematical finance. We do not follow the market; we model its underlying reality. We are seeking a Quantitative Software Engineer to architect the next generation of our autonomous intelligence platform. The Mandate In this role, you aren't just writing code; you are building the firm's primary engine for alpha generation. You will sit at the nexus of high-performance systems and advanced machine learning, responsible for the end-to-end delivery of mission-critical trading infrastructure. • Architect & Scale: Design high-throughput, low-latency distributed systems capable of training and deploying complex models on petabytes of real-time data., • Engineer Intelligence: Bridge the gap between theoretical research and production-grade execution by optimizing neural architectures for high-stakes financial environments., • Academic Excellence: A Bachelor's or Master's in Computer Science from a global Top-Tier institution (the 0.1% of your graduating class)., • Elite Technical Experience: A background at a Tier-1 technology firm leading high-impact initiatives in AI, Large Language Models (LLMs), or large-scale distributed systems., • Founder Mindset: Preference for those who have founded a technology startup or held a leadership role in an early-stage, high-growth venture. We value the "full-stack" ownership and the ability to solve ambiguous problems without a playbook., • Systemic Mastery: Expertise in high-performance languages (C++, Java) and modern AI frameworks (Python, PyTorch). You have a visceral understanding of how to optimize code for both speed and scale., • Fintech Intuition: A background in high-growth fintech or systematic trading is an advantage, but we value raw intellectual horsepower and engineering elegance above all else.Why This is the Apex Opportunity, • Direct P&L Impact: Unlike Big Tech, where your impact is diluted across millions of users, your work here directly dictates the firm's success. Your compensation is mathematically tied to the value you create., • Radical Autonomy: We operate in small, highly autonomous "cells." You will have the budget, the compute power, and the freedom to disrupt any part of our stack.

Job Description We are a cutting-edge technology company at the forefront of the Artificial Intelligence (AI) revolution. Our mission is to create intelligent solutions that transform industries and drive innovation. We are seeking a talented and motivated Prompt Engineer to join our dynamic team and play a pivotal role in shaping the future of AI. Role Overview: As a Prompt Engineer, you will be a key member of our AI development team, responsible for designing and developing high-quality prompts that drive our AI models and algorithms. Your expertise in crafting effective and engaging prompts will be essential in enhancing the performance and capabilities of our AI systems. Responsibilities: • Collaborate with AI researchers and developers to understand project requirements and objectives., • Design and create a diverse range of prompts tailored to specific AI tasks and applications., • Develop creative and innovative ways to generate effective prompts that improve model performance., • Conduct extensive research to identify and curate relevant data sources for prompt development., • Ensure the prompts are designed to elicit desired responses and achieve the desired outcomes., • Optimize and fine-tune prompts based on continuous testing and feedback from AI models., • Analyze AI model outputs and make data-driven adjustments to improve prompt efficacy., • Stay up-to-date with the latest advancements in natural language processing and AI technologies., • Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree preferred., • Proven experience in working with natural language processing and AI technologies., • Strong understanding of AI models, algorithms, and neural networks., • Experience in prompt engineering, creative writing, or content creation is a plus., • Proficiency in programming languages such as Python or JavaScript., • Solid knowledge of data collection, preprocessing, and annotation for prompt development., • Familiarity with machine learning frameworks and libraries like TensorFlow, PyTorch, or Hugging Face., • Strong analytical and problem-solving skills with a keen eye for detail., • Excellent communication and collaboration skills to work effectively in a team environment.

Job Description About Us Daat Lab is an AI venture studio that collaborates directly with businesses to transform deep domain expertise into valuable, commercial-grade AI products. We assist companies in identifying and validating high-impact, AI-feasible use cases. Our process spans from initial ideation and building a proof of concept to developing a fully commercializable product and successfully launching it in the market. We maintain an active presence across multiple sectors, including real estate, digital marketing/e-commerce, and health, with an ambitious goal of adding one new product to our portfolio every month. About the Role We are seeking a Technical Lead to drive product development from initial concept to launch, maintaining a strong customer focus. This is a highly hands-on role where you will thrive in ambiguity and be responsible for the full product lifecycle across multiple projects simultaneously. You will collaborate directly with our strategy and business teams to identify high-value, AI-feasible opportunities and influence product direction through rapid execution, including discovery, prototyping, building, shipping, and iteration. What You’ll Do: • Own multiple projects from end to end: brainstorming product concepts, generating POCs to be evaluated and owning builds to reach a minimum viable product., • Build full-stack applications (backend, frontend, data layer, infra, deployment, and monitoring)., • Experiment with AI functionality on each case: classical ML when needed (forecasting, scoring, classification), plus LLM/agent workflows and evaluation loops, • Establish engineering standards: code quality, CI/CD hygiene, logging/analytics, basic security, • Work directly with design partners and ship weekly updates, • You should have:, • 6+ years shipping full-stack products end-to-end, • Strong Python and modern web stack (React/Next.js + APIs + DB + deployments), • Data processing and Machine learning fundamentals (pandas, Sklearn, pytorch/tensorflow, model evaluation), • Experience building with LLMs and Agent frameworks (Open AI SDK, Google ADK, Langchain/Langraph, MCP), • Comfort with ambiguity, fast cycles, and customer-facing iteration, • Team leadership experience (manager/tech lead), • What Success Looks Like:, • Ship multiple POCs that clearly validate feasibility and ROI, • Bring at least one concept to a usable MVP with design-partner feedback loops, • Salary: $160 - 200k (full-time hire, will start as a 1099 contractor) Please note: Daat Lab is a separate entity, unrelated to Alchemy Worx.

Job Description Senior Cloud Architect – Data, AI & GenAI Platforms Location: US / Canada (Remote/Hybrid) Type: Contract / Full-Time Overview: We are hiring a Senior Cloud Architect to drive the design and implementation of modern data and AI platforms. This role will enable enterprise adoption of AI/ML and GenAI solutions through scalable cloud architectures. Key Responsibilities: • Build and scale cloud-native data and AI platforms, • Architect data pipelines and AI/ML integration frameworks, • Ensure governance, security, and operational excellence, • Strong experience in cloud architecture (AWS, Azure, GCP), • Expertise in large-scale data platform design and implementation, • Data platforms: Databricks, Snowflake, Azure Synapse, BigQuery, • ML/AI Engineering: Python, PyTorch, MLOps pipelines, • GenAI: Experience with LangChain, LLM orchestration, agentic AI

Job DescriptionHinge is the dating app designed to be deleted In today's digital world, finding genuine relationships is tougher than ever. At Hinge, we’re on a mission to inspire intimate connection to create a less lonely world. We’re obsessed with understanding our users’ behaviors to help them find love, and our success is defined by one simple metric– setting up great dates. With millions of users across the globe, we’ve become the most trusted way to find a relationship, for all. About the Role Join Hinge as a Machine Learning Engineer on the Trust & Safety team, where you'll apply AI and machine learning to mitigate the impact of policy violating actors, remove harmful content, and keep our users safe on the platform. Working alongside an established Trust & Safety AI team, you'll partner with product managers, data scientists, engineers, and analysts to build, deploy, and improve detection systems that have a direct, measurable impact on user safety. This is a high-ownership IC role on a small team with a large mission. You'll own the end-to-end lifecycle of ML projects, contribute to a growing portfolio of AI-powered safety features, and grow alongside senior engineers, all while playing a foundational role in how Hinge applies machine learning to give users a safer experience on their journey to find intimate connection.Responsibilities * Build, deploy, and maintain end-to-end machine learning models that detect policy violating actors, remove harmful content, and keep users safe. * Own medium-sized projects end-to-end (from problem scoping and data collection to training, deployment, monitoring, and iteration). * Contribute to scalable inference and data pipelines (e.g., Spark, Kubernetes), including preprocessing, batch and real-time inference, and post-processing components. * Apply standardized performance metrics, testing protocols, and evaluation processes to measure model effectiveness and identify risks. * Continuously assess and refine deployed models using user feedback, business impact signals, and emerging policy and ethical considerations. * Collaborate closely with Data Scientists, Data Engineers, Product Managers, Backend Engineers, and the AI Platform team to ship coordinated user safety improvements. * Stay current on advances in AI/ML, particularly LLMs and evaluation methods, and apply appropriate techniques to detection and user safety problems. What We're Looking For * Strong programming skills: Proficiency in Python and SQL, comfort with at least one ML stack (e.g., PyTorch, Hugging Face Transformers), and a working understanding of data pipelines. * Domain expertise: Solid understanding of machine learning, deep learning, and emerging AI techniques. Track record of building, debugging, and fine-tuning ML models for user-facing products. Experience with content classification, fraud detection, or related Trust & Safety problems is a plus. * System design & architecture: Experience training and deploying ML models in production. Working understanding of distributed computing for inference and training. * AI application: Hands-on with AI agents, RAG, structured outputs, and function/tool calling. Understands when to reach for an agent or LLM vs. a classical ML approach. * Evaluation frameworks for ML and LLM systems: Comfort designing and running evaluations to measure model effectiveness, fairness, and safety across both classical ML and LLM systems. Familiar with golden datasets, LLM-as-judge patterns, precision/recall/F1, false positive rates, hallucination, and offline/online metrics. * Cloud and data platform proficiency: Hands-on with at least one cloud environment (GCP, AWS, or Azure). Familiarity with Databricks, Ray, or Kubeflow is a plus. * Data engineering knowledge: Comfortable handling large datasets, including cleaning, preprocessing, and storage, and contributing to batch and streaming pipelines orchestrated with tools like Databricks or Argo. * Project ownership: Demonstrated ability to drive medium-sized projects to completion, identify and unblock yourself on technical issues, and ship measurable outcomes with limited oversight. * Collaboration and communication skills: The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds. * Strong written communication: The ability to communicate complex ideas and technical knowledge through Prior Experience * 2+ years of experience as an MLE, applied scientist, or data scientist (depending on education). * 1+ years of experience applying end-to-end machine learning models in an industry setting — including data collection, model training, deployment, and monitoring. * Experience integrating or evaluating LLMs in real-world applications with appropriate baseline metrics and evaluation methodologies is a plus. * Familiarity with at least one ML infrastructure component (feature store, training environment, model serving, observability, workflow orchestrator). * Previous exposure to Trust & Safety, fraud detection, content classification, or compliance is preferred but not required. * Demonstrated use of modern AI tooling in their actual workflow (e.g., Cursor, Claude Code, Codex). * A degree in computer science, engineering, or a related field (or equivalent practical experience). Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary range is reflective of a position based in New York City. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting.As a member of our team, you’ll enjoy: 401(k) Matching: We match 100% of the first 10% of pre-tax 401(k) contributions you make, up to a maximum of $10,000 per year. Professional Growth: Get an annual Learning & Development stipend once you’ve been with us for three months. You also get free access to Udemy, an online learning and teaching marketplace with over 6000 courses, starting your first day. Parental Leave & Planning: When you become a new parent, you’re eligible for 100% paid parental leave (20 paid weeks for both birth and non-birth parents.) Fertility Support: You’ll get easy access to fertility care through Carrot, from basic treatments to fertility preservation. We also provide a stipend towards fertility preservation. You and your spouse/domestic partner are both eligible. Date Stipend: All Hinge employees receive a $100 monthly stipend for epic dates– Romantic or otherwise. Hinge Premium is also free for employees and their loved ones. ERGs: We have eight Employee Resource Groups (ERGs)—Asian, Unapologetic, Disability, LGBTQIA+, Raices, Women/Nonbinary, Parents —that hold regular meetings, host events, and provide dedicated support to the organization & its community. At Hinge, our core values are… Authenticity: We share, never hide, our words, actions and intentions. Courage: We embrace lofty goals and tough challenges. Empathy: We deeply consider the perspective of others. Diversity inspires innovation Hinge is an equal-opportunity employer. We value diversity at our company and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We believe success is created by a diverse workforce of individuals with different ideas, strengths, interests, and cultural backgrounds. If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please let your Talent Acquisition partner know. #Hinge .

Job Description About the Role: We are in search of an exceptional Machine Learning Engineer to join our accomplished team. In this role, you will take the lead in developing and fine-tuning predictive ML models, with a primary focus on Ad Score and Ad Account Health. You will play a crucial part in delivering actionable insights and solutions to our clients, and your work will be integral to our mission. Responsibilities include but are not limited to; • ML Model Development: Lead the development and refinement of predictive ML models, particularly Ad Score and Ad Account Health., • Data Analysis: Conduct in-depth data analysis to identify trends, patterns, and insights that inform model development and optimization., • Feature Engineering: Collaborate with data engineers to create and maintain feature engineering pipelines to support model training., • Model Evaluation: Implement rigorous evaluation methodologies to assess model performance, making necessary adjustments for continuous improvement., • Deployment and Integration: Work closely with engineering teams to deploy models and integrate them into our products through APIs., • Collaboration: Collaborate closely with product managers, full-stack engineers, and TPMs to ensure seamless integration of data science solutions into our products., • Master's or Ph.D. in a related field with a strong academic background., • Proven experience as a Data Scientist with a track record of developing and deploying predictive ML models., • Expertise in machine learning techniques, including but not limited to regression, classification, clustering, and deep learning., • Proficiency in data manipulation, feature engineering, and model evaluation., • Strong programming skills in languages such as Python and experience with libraries like TensorFlow, PyTorch, or scikit-learn., • Excellent communication skills and the ability to collaborate effectively within cross-functional teams., • A passion for continuous learning and staying updated with the latest trends and technologies in data science., • Strong problem-solving abilities and the capacity to translate complex data into actionable insights.Required knowledge of:, • Python, • SQL, • Cloud Platforms (GCP, AWS, Azure), • Data Warehouses (BigQuery, Snowflake, Redshift), • LLMs / AI APIs, • Git / GitHubNice to have:, • Data Transformation (dbt), • Semantic Layers (Cube, Looker, dbt Metrics), • TypeScript, • Bayesian modeling experience - ideally Marketing Mix Models (PyMC, Stan, or similar..). Understands priors, MCMC sampling, posterior diagnostics., • Causal inference / experimentation- geo experiments (matched markets), A/B testing at scale. Familiar with incrementality measurement., • Marketing/advertising domain- understanding of attribution, media channels (paid social, search, display, video), campaign structures., • Unlimited vacation policy, • Monthly Phone Stipend, • Comprehensive Medical, Dental, and Vision insurance options, • 401(K) plan with matching, • Dog friendly office, • Hybrid work opportunity, • Professional Development Program, • Bonus Perk - Seamless allowance Total compensation based on education, experience, and skills level ($90,900-$254,100) * Level 1 - Possesses essential capabilities * $90,900-$123,540 * Level 2 - Possesses developing capabilities * $123,540-$156,180 * Level 3 - Possesses notable capabilities. * $156,180-$188,820 * Level 4 - Possesses strong capabilities. * $188,820-$221,460 * Level 5 - Possesses advanced capabilities. * $221,460-$254,100 About WITHIN WITHIN is the world's first Performance Branding company, partnering with some of the biggest brands in the world to drive business growth through innovative marketing strategies. Our integrated operating model collapses the traditional marketing silos between creative and media, performance and brand, and across media channels. With a full suite of offerings including media, creative, SEO, Lifecycle, Retail Media, Affiliate and Influencer, we're able to work with our brand partners in an integrated fashion, allowing us to align marketing strategies back to core business objectives. Client teams at WITHIN are trained on how to always act as a trusted business partner, acting as a fiduciary to client needs above our own. Teams at WITHIN have the ability to work with iconic brands such as The North Face, Timberland, Ben and Jerry's and Jose Cuervo. Everyone at WITHIN wants to grow and be challenged. It's a collaborative place made up of small, closely knit and versatile teams that are fast and adaptive to solve problems and build systems. Check out some of our work! We weave AI into everything we do, using the latest tech across all teams to innovate, work smarter, and make better decisions. Whether it's in creative, operations, or anything else, AI helps us level up and do things at a whole new scale. We expect our people to use AI in their daily work, fully embracing it as a critical tool to help us succeed. Join Our Network! Stay connected with us and be the first to know about new opportunities, industry insights, and updates. Follow us on: • LinkedIn, • WhatsApp Community, • Instagram, • New York City: 43-01 22nd St, Suite 602, Queens, NY 11101, United States, • Bogotá: WeWork Av. Carrera 19 #100-45 Usaquén, Piso (Floor) 10, Bogotá, Distrito Capital de Bogotá 110111, Colombia, • Mexico City: Av. Insurgentes Sur 1082, Piso (Floor) 2, Oficina 2008, Ciudad de México, CDMX 03100, México

Job Description Location: New York, NY Our client is a distinguished global provider of legal services. This is a full-time, direct hire onsite role requiring US Citizenship or Green Card. We are seeking a Legal Practice Technology Data Scientist. This position can be in San Francisco, Los Angeles, Chicago, or New York – relocation assistance is not offered. If you have spent your career in eDiscovery and litigation support and are ready to apply that foundation, along with a broader technical skill set, to a wider scope of work, this could be the role for you. Data Scientists sit within a group of discovery, data management, and AI specialists dedicated to designing and executing client-focused workflows on some of the most complex matters in our industry. You will report to the Associate Director of Technical Operations. The role is hands-on and client-facing; more than half of your time will be spent directly embedded in active matters. This position sits within the firm’s Innovation Program. Our client upholds strict performance standards and fosters a culture focused on continuous growth. Individuals who exhibit initiative and dedication will be offered opportunities for increased responsibilities and long-term professional advancement within the organization. Must be a U.S. Citizen or Green Card holder – sponsorship is not available Desired Qualifications and Experience: • Bachelor’s degree, • 3+ years of experience in a law firm, legal services, or professional services organization with significant experience working in a team environment., • Ability to translate complex concepts into client-friendly language., • Highly analytical with strong problem-solving skills and the ability to translate ambiguous problems into structured solutions., • Knowledge of statistical analysis and data modeling., • Demonstrated hands-on experience with Relativity custom development. Deep knowledge in eDiscovery-focused data processing, structured analytics, and related troubleshooting., • Expert-level proficiency in Microsoft Excel, including VBA development, Power Query, complex formula construction, advanced data modeling, and chart design., • Experience in creating data visualizations with hands-on proficiency in tools such as Plotly, Tableau, and Microsoft Power BI., • Strong Python skills for data analysis, statistical modeling, and AI/ML prototyping (e.g., pandas, PyTorch, TensorFlow); advanced SQL proficiency; experience building data pipelines., • Proficiency in front-end web technologies including JavaScript, HTML, and CSS, with the ability to develop interactive web-based tools and dashboards., • Hands-on experience with AI platforms and tools (e.g., OpenAI, Microsoft Azure OpenAI, Hugging Face, LangFlow, LangChain), including practical implementation of RAG pipelines, vector databases, and knowledge graph construction., • General knowledge of social network analysis, natural language processing, classification algorithms, and image processing., • Familiarity with git, svn, JIRA, or other version control technologies., • Familiarity with hardware platforms (e.g., CPUs, GPUs, FPGAs)., • Familiarity with leading legal technology platforms is preferred (docketing systems, document management systems, case management systems, eDiscovery, data collection and web capture solutions)., • Experience evaluating LLM output quality through benchmarking, precision, recall, and extraction accuracy assessment is preferred. Summary of Responsibilities: Coordination and Execution of In-house Solution Development. You will support the collection of requirements and the design and building of in-house solutions. You will consult with case teams on data strategies and execute rapid solution development including custom scripting, data management, database development, and visualization design. You will complete requests requiring advanced technologies such as document layout analysis, LLM-based information extraction, semantic chunking, and entity recognition, while maintaining comprehensive documentation throughout. Data Project Service Delivery. You will support matter-specific needs as a subject matter resource, analyzing and troubleshooting data processing and analytics issues. You will develop custom eDiscovery workflows and execute data-heavy, data-modeling projects that require creative problem-solving and technical depth. Department Initiatives. You will work closely with other data science teams and Legal Practice Technology (“LPT”) leadership to evaluate and test internal solutions and emerging technology. You will serve as a go-to resource for technical knowledge in AI, contributing your expertise to the team’s continuous advancement of its capabilities. How to Apply: Our client has hired us to help facilitate the initial interview and recruiting process. Please attach your current version of your resume and make sure you complete our initial pre-screening questions that will be used for determining which applicants will be considered at this time. Thank you for your interest. Company DescriptionWe Place People is a premiere Executive Search Firm working with leading companies nationwide. We have a direct relationship with our clients and a 95% hire rate! We differentiate ourselves from other firms & work closely with our candidates throughout the interview process. WE PLACE PEOPLE is what we do best!We Place People is a premiere Executive Search Firm working with leading companies nationwide. We have a direct relationship with our clients and a 95% hire rate! We differentiate ourselves from other firms & work closely with our candidates throughout the interview process. WE PLACE PEOPLE is what we do best!