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Job Description Founding Quantitative Researcher About the Role We’re building an AI-native wealth management platform to transform how financial advisors serve their clients. Despite trillions of assets under management, the industry still relies on manual processes that limit outcomes. Backed by world-class investors and advisors, our founding team brings deep experience from top fintech and AI companies. As our Founding Quantitative Researcher, you’ll play a pivotal role in shaping our core technology and driving real impact on the future of wealth management. What You’ll Own • Portfolio optimization algorithms balancing return, risk, and tax efficiency., • Machine learning models that personalize investment strategies at scale., • Quantitative research powering the AI-driven advisor platform., • Advisor relationships to translate real-world needs into research and product improvements. What We’re Looking For • 7+ years as a quantitative researcher at a Tier 1 fund (or 3+ years with an advanced degree)., • Proven experience developing and implementing systematic strategies (not just academic research)., • Strong background in portfolio optimization, risk modeling, or systematic strategies. Education • PhD in Finance, Mathematics, Economics, Physics, or Computer Science strongly preferred., • Exceptional candidates with 7+ years applied experience may substitute for a PhD. Skills • Full-stack quantitative fluency with strong fundamentals in modern frameworks., • Expertise in AI/ML applications to investment strategies., • Advanced coding skills; able to iterate quickly (“vibe coding” mindset)., • Thrives in the chaos of early-stage startups; embraces ambiguity., • High EQ and maturity; collaborative and eager to mentor in a flat team structure., • Strong product sense and communication skills to engage directly with advisors., • Demonstrated high slope (intrinsic motivation, ambition, and drive). This is a rare opportunity to join as a founding team member at the intersection of fintech and AI. You’ll directly shape industry-defining technology, have ownership over core algorithms, and see your work translate into better financial outcomes for millions of clients.

Job Description Perplexity is an AI-powered answer engine founded in December 2022 and growing rapidly as one of the world's leading AI platforms. Perplexity has raised over $1B in venture investment from some of the world's most visionary and successful leaders, including Elad Gil, Daniel Gross, Jeff Bezos, Accel, IVP, NEA, NVIDIA, Samsung, and many more. Our objective is to build accurate, trustworthy AI that powers decision-making for people and assistive AI wherever decisions are being made. Throughout human history, change and innovation have always been driven by curious people. Today, curious people use Perplexity to answer more than 780 million queries every month–a number that's growing rapidly for one simple reason: everyone can be curious. We are hiring for an experienced Data Scientist to accelerate our growth initiatives and help Perplexity expand its reach globally. You'll work closely with our Growth, Marketing, Product, Enterprise, and Partnership functions, using data-driven insights to optimize strategies across paid acquisition, organic growth, product development, retention, monetization, and strategic partnerships. This role offers the chance to significantly influence how our growth strategies evolve and scale in a dynamic startup environment. Responsibilities • Collaborate closely with Growth, Marketing, Product, Enterprise, and Partnership teams to provide data-driven insights and recommendations across all growth initiatives., • Perform deep-dive analyses on user behavior, conversion funnels, and retention patterns to drive both paid and organic growth., • Lead user research and segmentation analysis to inform growth strategies, market targeting, product development, and paid campaign optimization., • Design, implement, and interpret A/B tests to continuously enhance marketing performance, product features, and overall user experiences., • Define, implement, and visualize key growth metrics across paid acquisition, organic channels, activation, retention, and monetization, creating dashboards to track business performance and marketing ROI., • Develop data models and pipelines to improve analytics efficiency, enable self-service analytics, and support strategic decision-making., • Support revenue growth initiatives through pricing analysis, subscription optimization, and enterprise growth strategies., • Analyze paid acquisition channels and campaigns performance, identifying opportunities for optimization, budget allocation, and sustainable growth., • Have 6-8+ years of experience working as a data scientist or related role with growth focus., • Have experience with growth disciplines including: paid acquisition, product marketing, SEO, social media, lifecycle marketing, product analytics, and/or conversion optimization., • Are proficient in SQL and experienced with BI and visualization tools (e.g., Omni, Mode, Hex, Looker)., • Have experience designing, implementing, and analyzing A/B tests and statistical experimentation., • Take ownership and are a self-starter who thrives with open-ended problems and cross-functional collaboration., • Previous experience at a high-growth startup or early-stage company in a growth-focused data science role., • Hands-on experience with dbt and data engineering/analytics engineering., • Experience with Snowflake and modern data stack tools., • Are comfortable with Python for data analysis and automation., • Machine learning experience, particularly in growth applications (LTV prediction, churn modeling, attribution modeling, recommendation systems). Final offer amounts are determined by multiple factors, including, experience and expertise, and may vary from the amounts listed above. Equity: In addition to the base salary, equity may be part of the total compensation package. Benefits: Comprehensive health, dental, and vision insurance for you and your dependents. Includes a 401(k) plan.

Job Description Perplexity is an AI-powered answer engine founded in December 2022 and growing rapidly as one of the world's leading AI platforms. Perplexity has raised over $1B in venture investment from some of the world's most visionary and successful leaders, including Elad Gil, Daniel Gross, Jeff Bezos, Accel, IVP, NEA, NVIDIA, Samsung, and many more. Our objective is to build accurate, trustworthy AI that powers decision-making for people and assistive AI wherever decisions are being made. Throughout human history, change and innovation have always been driven by curious people. Today, curious people use Perplexity to answer more than 780 million queries every month–a number that's growing rapidly for one simple reason: everyone can be curious. We are looking for an AI Inference engineer to join our growing team. Our current stack is Python, Rust, C++, PyTorch, Triton, CUDA, Kubernetes. You will have the opportunity to work on large-scale deployment of machine learning models for real-time inference. Responsibilities • Develop APIs for AI inference that will be used by both internal and external customers, • Benchmark and address bottlenecks throughout our inference stack, • Improve the reliability and observability of our systems and respond to system outages, • Experience with ML systems and deep learning frameworks (e.g. PyTorch, TensorFlow, ONNX), • Familiarity with common LLM architectures and inference optimization techniques (e.g. continuous batching, quantization, etc.) Final offer amounts are determined by multiple factors, including, experience and expertise, and may vary from the amounts listed above. Equity: In addition to the base salary, equity may be part of the total compensation package. Benefits: Comprehensive health, dental, and vision insurance for you and your dependents. Includes a 401(k) plan.

Job DescriptionAI Research Scientist (Test Time Compute) | naptha.ai About the role We are seeking an exceptional AI Research Scientist to join Naptha AI at the ground floor, focusing on advancing the state of the art in test time compute optimization for large language models. In this role, you will be responsible for researching and developing novel approaches to improve inference efficiency, reduce computational requirements, and enhance model performance at deployment. Working directly with our technical team, you will help shape the fundamental architecture of our inference optimization platform. This role is critical in solving core technical challenges around model compression, efficient inference strategies, and deployment optimization. You will work at the intersection of machine learning, systems optimization, and hardware acceleration to develop practical solutions for real-world model deployment and scaling. Core ResponsibilitiesResearch & Development * Design and implement novel architectures for efficient model inference * Develop frameworks for model compression and quantization * Research approaches to optimize test-time computation across different hardware * Create efficient protocols for distributed inference and resource management * Implement and test new ideas through rapid prototyping Technical Innovation * Stay at the forefront of developments in ML efficiency and inference optimization * Identify and solve key technical challenges in model deployment * Develop novel approaches to model compression and acceleration * Bridge theoretical research with practical implementation * Contribute to the academic community through publications and open source Platform Development * Help design and implement efficient inference pipelines * Develop scalable solutions for model deployment and serving * Create tools and frameworks for performance monitoring and optimization * Collaborate with engineering team on implementation * Build proofs of concept for new optimization techniques Leadership & Collaboration * Work closely with engineering team to implement research findings * Mentor team members on advanced optimization techniques * Contribute to technical strategy and roadmap * Collaborate with external research partners when appropriate * Help evaluate and integrate external research developments In this role, you're a good fit if you have: * Strong background in machine learning and systems optimization * Deep understanding of model compression and efficient inference techniques * Hands-on experience with modern ML frameworks and deployment tools * Experience with ML infrastructure and hardware acceleration * Track record of implementing efficient ML systems * Excellent programming skills (Python required, C++/CUDA a plus) * Strong analytical and problem-solving abilities * PhD in Machine Learning, Computer Science, Mathematics, or equivalent experience is a plus * Published research in relevant fields is a plus Required Technical Experience: * Python programming and ML frameworks (PyTorch, TensorFlow) * Experience with model optimization techniques (quantization, pruning, distillation) * MLOps and efficient model deployment * Hardware acceleration (GPU, TPU optimization) * Version control and collaborative development * Experience with large language models About the hiring process: * Initial technical interview * Research presentation * System design discussion * Technical challenge * Team collaboration interview Compensation & Benefits: * Competitive salary with significant equity stake * Remote-first work environment * Full medical, dental, and vision coverage * Flexible PTO policy * Learning and development budget * Conference and research publication support * Home office setup allowance Additional Notes: * Must be comfortable with ambiguity and rapid iteration typical of pre-seed startups * Strong bias for practical implementation of research ideas * Passion for advancing the field of efficient ML systems * Interest in open source contribution and community engagement Naptha AI is committed to building a diverse and inclusive workplace. We are an equal opportunity employer and welcome applications from all qualified candidates regardless of background.

Job Description IP Litigation Associate Location: Northern California Salary: $250,000 to $340,000 base salary Schedule: Big law billables, 1900 to 2000+ annual expectation, bonus based on exceeding this and other individual and group goals A prestigious law firm with one of the nation’s most active intellectual property litigation practices is seeking a highly qualified associate with 3–4 years of experience for its fast-growing west coast IP litigation team. The firm is renowned for handling groundbreaking patent, trade secrets, and commercial disputes in the high technology, software, digital media, and semiconductor industries. Key Skills & Experience Required: • At least 3 years of experience in practice with specialty litigating on intellectual property and patent development, protecting clients' interests in IP and developing novel technology and modern marvels in life sciences, computer science, artificial intelligence, learning language model development, machine learning, etc., • Experience preparing or responding to reviews from multi-disciplinary groups on proposed filings for submission to the IP & Patent courts., • Strong academic credentials and prior experience at a top law firm., • Graduate degree in specialty of interest required with active USPTO registration. Patent bar is preferred, • Must be admitted to the state bar or with eligibility to waive in. The information contained herein is provided for informational purposes only and does not constitute legal advice or create an attorney-client relationship. All materials are the property of People Placers and may not be reproduced, distributed, transmitted, cached or otherwise used without the prior written permission of Percy Towers. People Placers is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, gender identity, sexual orientation, national origin, disability, or protected veteran status. This post is an advertisement for a client and does not constitute a full or comprehensive description of the role. Inquire within for more information.

Job DescriptionAbout Us Essential AI is building an open platform to fuel and accelerate AI breakthroughs globally. Our open models, robust tooling, reproducible pipelines, and evaluation frameworks are designed for collaboration and contribution, empowering others to build, iterate, and innovate faster. Essential AI's technology and products have the means to shape AI advancements while supporting scalable and sustainable business models. Powerful AIs don't trace their origins to singular breakthroughs, but from an amalgam of improvements, incremental and large. Essential AI creates the ideal environment to catalyze these advancements, enabling a steady path to sustained frontier capabilities. The Role The ML Infra Platform Engineer will be responsible for architecting and building the compute infra that powers the training and serving of our models. This requires a full understanding of the complete backend stack → from frameworks to compilers to runtimes to kernels. Running and training models at scale often requires solving novel system problems. As an Infra Systems Engineer, you'll be responsible for identifying these problems and then developing systems that optimize the throughput and robustness of distributed systems. With proven experience building large-scale platforms, you will be responsible for building and advancing our systems that allow research and engineering organizations to iteratively develop, test, and deploy new features reliably, with high velocity, and with a frictionless-fast development cycle. What you’ll be working on * You will help oversee and drive the vision of how we should build, test, and deploy models, while taking ownership and transform state-of-the-art development experience for research * Design, build, and maintain scalable machine learning infrastructure to support our model training, inference and applications * Design and implement scalable machine learning and distributed systems that enable training and scaling of LLMs. Work on parallelism methods improve training of in a fast and reliable way * Working on lower levels of the stack to build high-performing and optimal training and serving infrastructure, including researching new techniques and writing custom kernels as needed to achieve improvements * Develop tools and frameworks to automate and streamline ML experimentation and management * Collaborate with other researchers and product engineers to bring magical product experiences through large language models * Be willing to optimize performance and efficiency across different accelerators What we are looking for * A strong understanding of architectures of new AI accelerators like GPU, TPU, IPU, HPU etc and their tradeoffs. Knowledge of parallel computing concepts and distributed systems. * Experience with Kernels, Low precision training, MoE. * Prior experience in performance tuning of training and/or inference LLM workloads. Experience with MLPerf or internal production workloads will be valued. * 6+ years of relevant industry experience in leading the design of large-scale & production ML infra systems. Experience with Communication Libraries. * Experience with training and building large language models using frameworks such as Megatron, DeepSpeed, etc and deployment frameworks like vLLM, TGI, TensorRT-LLM etc * Comfortable with working under-the-hood with kernel languages like OAI Triton, Pallas and compilers like XLA * Experience with INT8/FP8 training and inference, quantization and/or distillation * Knowledge of container technologies like Docker and Kubernetes and cloud platforms like AWS, GCP, etc. * Intermediate fluency with network fundamentals like VPC, Subnets, Routing Tables, Firewalls etc We encourage you to apply for this position even if you don’t check all of the above requirements but want to spend time pushing on these techniques. Essential AI commits to providing a work environment free of discrimination and harassment, as well as equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. You may view all of Essential AI’s recruiting notices here, including our EEO policy, recruitment scam notice, and recruitment agency policy.

Job DescriptionAI Research Scientist (Multi-agent Systems) | naptha.ai About the role We are seeking an exceptional AI Research Scientist to join Naptha AI at the ground floor, focusing on advancing the state of the art in multi-agent systems and agent interoperability. In this role, you will be responsible for researching and developing novel approaches to agent collaboration, coordination, and scalability. Working directly with our technical team, you will help shape the fundamental architecture of our agent interoperability platform. This role is critical in solving core technical challenges around agent communication protocols, task delegation, and distributed intelligence. You will work at the intersection of multi-agent systems, machine learning, and distributed systems to develop practical solutions for real-world agent deployment and collaboration. Core ResponsibilitiesResearch & Development * Design and implement novel architectures for scalable multi-agent systems * Develop frameworks for agent communication and coordination * Research approaches to improve agent interoperability across different frameworks * Create efficient protocols for distributed task execution and resource management * Implement and test new ideas through rapid prototyping Technical Innovation * Stay at the forefront of developments in multi-agent systems and AI research * Identify and solve key technical challenges in agent interoperability * Develop novel approaches to agent collaboration and task delegation * Bridge theoretical research with practical implementation * Contribute to the academic community through publications and open source Platform Development * Help design and implement core platform architecture * Develop scalable solutions for agent deployment and management * Create tools and frameworks for agent monitoring and evaluation * Collaborate with engineering team on implementation * Build proofs of concept for new capabilities Leadership & Collaboration * Work closely with engineering team to implement research findings * Mentor team members on advanced ML concepts and techniques * Contribute to technical strategy and roadmap * Collaborate with external research partners when appropriate * Help evaluate and integrate external research developments In this role, you're a good fit if you have: * Strong background in machine learning and AI research * Deep understanding of multi-agent systems and reinforcement learning * Hands-on experience with modern agent frameworks (e.g., LangChain, AutoGPT) * Experience with ML infrastructure and deployment * Track record of implementing complex AI systems * Excellent programming skills (Python required, Rust a plus) * Strong analytical and problem-solving abilities * PhD in Machine Learning, Physics, Mathematics, or equivalent experience is a plus * Published research in relevant fields is a plus Required Technical Experience: * Python programming and ML frameworks (PyTorch, TensorFlow) * Experience with agent frameworks (LangChain, AutoGPT, etc.) * MLOps and model deployment * Distributed systems and scalable architecture * Version control and collaborative development * Experience with large language models About the hiring process: * Initial technical interview * Research presentation * System design discussion * Technical challenge * Team collaboration interview Compensation & Benefits: * Competitive salary with significant equity stake * Remote-first work environment * Full medical, dental, and vision coverage * Flexible PTO policy * Learning and development budget * Conference and research publication support * Home office setup allowance Additional Notes: * Must be comfortable with ambiguity and rapid iteration typical of pre-seed startups * Strong bias for practical implementation of research ideas * Passion for advancing the field of multiagent systems * Interest in open source contribution and community engagement Naptha AI is committed to building a diverse and inclusive workplace. We are an equal opportunity employer and welcome applications from all qualified candidates regardless of background.

Job Description Member of Technical Staff – Backend Full-time | On-site | San Francisco, CA About the Role We’re seeking a Backend Engineer (Member of Technical Staff) with 5+ years of experience to design and build core systems that power large-scale AI and data processing capabilities. This is a foundational engineering role with high visibility and ownership, ideal for someone who enjoys solving deep technical problems and building scalable systems from the ground up. You’ll play a central part in developing backend infrastructure that supports machine learning pipelines, structured data extraction, and production-grade applications used by customers in finance and operations. What You’ll Do • Build Core Systems: Design and implement backend systems that deploy and scale machine learning capabilities for both training and production., • Architect for Scale: Lead architectural decisions that enable rapid iteration and robust performance across user-facing and internal systems., • Extract and Structure Data: Develop systems that transform complex financial and tax documents into high-quality structured data., • Integrate ML and Applications: Connect machine learning inference, monitoring tools, and LLM interactions with business logic and application layers., • Collaborate Cross-Functionally: Work with accountants, product teams, and engineers to translate real-world needs into reliable, efficient solutions., • Optimize Infrastructure: Enhance CI/CD pipelines and database systems for performance, scalability, and seamless vendor API integrations. Who You Are • 5+ years of experience in backend software development, ideally in high-performance or data-heavy environments., • Strong proficiency in Python and modern backend frameworks., • Experience designing scalable, maintainable systems and APIs., • Deep understanding of databases, data modeling, and system reliability., • Comfortable operating in fast-paced, high-ownership settings where clarity evolves rapidly., • Prior experience working with machine learning infrastructure or structured data pipelines is a plus. Work Environment • Location: Union Square, San Francisco, • Schedule: On-site, 5 days per week, • Culture: Collaborative, high-ownership environment working alongside experienced technical leaders and early engineers. Compensation & Benefits • Salary: $200K–$325K, • Equity: Stock options included, • Visa Sponsorship: Available, • Benefits: Comprehensive package including healthcare, PTO, and opportunities for professional growth. Ready to take the next step? Apply now or email Jenn at to learn more.

Job Description Founding Engineer Full-time | On-site | San Francisco, CA About the Role We’re looking for a Founding Engineer with a strong backend engineering background to design and scale the systems powering real-time AI and compliance workflows in fintech. You’ll architect and own the critical infrastructure that drives high-performance, low-latency experiences while working side by side with the founding team to shape both the technical and product direction. This is a rare opportunity to be a ground-floor engineer at a fast-moving startup operating in a regulated space — solving high-stakes problems in performance, reliability, and compliance. What You’ll Do • Own Core Systems: Architect, build, and operate resilient backend systems supporting real-time AI and compliance workflows., • Design Integrations: Build APIs that interface with financial platforms, payment processors, and compliance systems., • Optimize Performance: Push performance limits to achieve sub-700ms latency at scale., • Deploy at Scale: Use Kubernetes, Kafka, and event-driven architectures to deliver fault-tolerant, distributed systems., • Ship Fast, Ship Right: Execute end-to-end — from whiteboard to live deployment in production environments., • Shape Product Direction: Partner closely with leadership to influence technical roadmap and feature priorities. Who You Are • 5+ years of backend engineering experience, with expertise in Python or similar high-performance backend languages., • Deep knowledge of AsyncIO, FastAPI/Django, Kafka, RabbitMQ, Redis Streams, Postgres, and Kubernetes., • Experience building distributed systems and optimizing for low-latency environments., • Thrives in a high-performance, fast-paced culture (expect long but rewarding hours)., • Bonus points for experience with AI/LLM systems, applied machine learning, or previous startup/founder experience. Work Environment • Location: On-site in San Francisco (Mission Bay), • Schedule: 6 days/week, 8 AM – 8 PM — ideal for those who love intensity, ownership, and speed., • Culture: Relentlessly focused on performance, precision, and execution. Compensation & Benefits • Salary: $150K – $230K (commensurate with experience), • Equity: 0.4% – 1% meaningful early-stage ownership, • Visa: STEM OPT and H1B transfers accepted, • Perks: Opportunity to define core architecture, shape company direction, and work with top technical and product leaders in AI and fintech Ready to take the next step? Apply now or email Jenn at to learn more.

Job Description At Philo, we're a group of technology and product people who set out to build the future of television, marrying the best in modern technology with the most compelling medium ever invented — in short, we're building the TV experience that we've always wanted for ourselves. In practice this means leveraging cloud delivery, modern tech stacks, machine learning, and hand-crafted native app experiences on all of our platforms. We aim to deliver a rock solid experience on the streaming basics, while cooking up next generation multi-screen and multi-user playback experiences. Senior Machine Learning Engineer (Recommendation Systems) Philo's recommendation system improves user engagement and customer satisfaction by tailoring content discovery to individual preferences and viewing habits. We want users to be confident that Philo will have something they want to watch every time they open the app. We are seeking a Senior Machine Learning Engineer to lead our content personalization efforts, shaping experiences that impact millions of users. In this role, you will research, design, and build advanced algorithms and large-scale systems that power Philo's recommendation engine. As a senior member of a growing team, you will tackle complex machine learning challenges and collaborate with data science, product, infrastructure, and backend engineering teams to deliver innovative, data-driven personalization solutions. Your work will directly impact content discovery, deepen user engagement, and drive long-term retention. Responsibilities: • Lead development of recommendation systems: Design, build, and optimize advanced algorithms for SVOD, Live TV, and FAST personalization., • Drive ML innovation at scale: Conduct deep dives into models and system components, ensuring performance, scalability, and robustness across regions and product areas., • Own the ML pipeline: Build and maintain reliable pipelines for data extraction, feature engineering, model training, testing, and deployment., • Collaborate with Product, Data Science & Engineering: Translate product requirements into ML solutions, set clear expectations, and deliver measurable improvements in user engagement., • Advance deep learning in recommendations: Apply frameworks such as TensorFlow, PyTorch, or similar to develop state-of-the-art recommendation models., • Experimentation: Conduct rigorous A/B testing and ML experiments to understand model performance and iterate rapidly based on feedback., • ML Vision and Roadmap: Contribute to the strategic planning of the recommendations roadmap, aligning engineering efforts with business objectives and user needs., • Explore advanced architectures: Experience with frameworks like Two-Tower models and Deep Cross Networks (DCN) is a strong plus. Qualifications: • 8+ years of experience in backend engineering and/or data science, including 4+ years focused on machine learning. Experience with recommendation systems is a big plus., • Strong coding skills in Python, as well as proficiency in using ML frameworks like PyTorch or TensorFlow., • Excellent analytical and problem-solving skills, with the ability to translate complex technical challenges into business solutions., • Proven track record of leading projects and delivering impactful machine learning solutions., • Strong communication and documentation skills; capable of explaining complex, technical concepts to non-technical stakeholders and to diligently document your work to help the team as a whole learn and move quickly., • Experience with Amazon SageMaker or similar MLOps platforms Status: Full-time Location: San Francisco, CA Compensation: Includes annual salary between $200K - $237K depending on experience and location, company stock options and health benefits. We value a diverse and inclusive workplace and we welcome people of different backgrounds, experiences, skills, and perspectives. Philo is an equal opportunity employer. We believe that everyone does their best work when they are supported by each other and the company, and we offer a generous set of benefits to make sure the Philo team is happy and healthy. Here is a sampling of the benefits we offer our team: • Full health, dental and vision coverage for you and your family, • 401(k) plan with employer contributions (we match 100% of deferrals up to 3% of pay and 50% of the next 2% of pay), • Flexible working hours, • Up to 20 weeks of fully paid parental leave, • Unlimited paid time off for vacation and sick leave, • $2,000 annual vacation bonus (we pay you to take a two week vacation), • $5,250 annually for professional development and educational assistance, • $1,250 annual home office + TV stipend during first year of employment ($250 annually thereafter), • $500/month ($6,000/year) bonus for employees who commit to working at least 3 days per week in our offices, plus generous commuter benefits ($315/month towards transit, rideshare, bike rental, or parking at our HQ office in San Francisco), • Free Gympass subscription — an all-in-one corporate benefit that gives employees the largest selection of gyms, studios, classes, training and wellness apps, • Dog-friendly office Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Job Description We are looking for an experienced Business Analyst to join our team in San Francisco, California. In this long-term contract role, you will play a critical part in identifying and mitigating fraud risks while ensuring a seamless customer experience. If you are skilled in fraud analytics, data analysis, and cross-functional collaboration, this opportunity will allow you to make a meaningful impact in a dynamic and fast-paced environment. This position is hybrid with 2 days onsite required. Responsibilities: • Monitor and analyze fraud metrics to identify trends and emerging risks., • Conduct in-depth investigations on flagged accounts and transactions to validate legitimate customers and reduce friction., • Develop and maintain dashboards and reports to track fraud KPIs using tools like Snowflake and Tableau., • Collaborate with cross-functional teams to identify gaps in payment and sign-up processes., • Provide actionable recommendations to reduce fraud losses and enhance detection accuracy., • Partner with stakeholders to refine fraud detection policies and workflows., • Translate data insights into strategic recommendations for business leaders., • Contribute to the development of scalable fraud prevention strategies while addressing immediate challenges., • Work closely with engineering and product teams to implement fraud solutions., • Stay informed about evolving fraud trends to proactively address potential vulnerabilities., • Minimum of 5 years of experience in fraud and risk analysis within SaaS, eCommerce, or FinTech industries., • Strong expertise in digital fraud prevention, payments risk, chargebacks, and account abuse., • Advanced proficiency in querying and analyzing large datasets using tools like Snowflake and Tableau., • Demonstrated ability to conduct detailed investigations and provide strategic insights., • Excellent communication skills, with a talent for presenting data-driven findings to senior leadership., • Familiarity with SQL and Snowflake is a plus., • Understanding of machine learning in the context and appllication of fraud., • Self-starter with the ability to manage workflows and deliver results independently., • Proven experience in collaborating with cross-functional teams to implement fraud prevention strategies.

Job DescriptionAssociate – Patent Prosecution (Electrical Engineering & Computer Science) Direct Counsel is representing an Amlaw 100 firm seeking a mid-level associate to join its Electrical Engineering and Computer Science Patent Prosecution Practice Group. This position is open to any firm location, with strong preference for Atlanta, Denver, Houston, St. Louis, Kansas City, Los Angeles, or San Francisco. The ideal candidate will have at least 3 years of experience in patent preparation and prosecution, along with a degree in electrical engineering, computer engineering, software engineering, computer science, or physics. Candidates must also demonstrate strong academic achievement, prior law firm, engineering, or industry experience, and excellent writing and communication skills. Preferred experience includes: * Patent prosecution in electrical engineering or software-related technologies, including: * Machine learning, artificial intelligence, or neural networks * Radio frequency (RF) circuitry * Hardware and/or communications security (e.g., encryption/decryption) Qualifications: * J.D. required * Active bar admission in the jurisdiction where the candidate intends to practice * USPTO admission required Compensation: Salary range between $240,000-$365,000 with additional discretionary bonus potential. Comprehensive benefits package includes medical, dental, vision, life, disability, 401(k), and paid time off.

Job DescriptionMember of Technical Staff - Applied AI / ML Engineer Location: San Francisco, CA (Union Square) Employment Type: Full-time Work Arrangement: On-site 5 days a week About the Role Our client is a GenAI-native platform that automates complex tax document processing, serving top accounting firms and wealth management offices. The platform was recently acquired by Thomson Reuters and is operating as a fast-paced, high-growth startup within a larger structure. They are seeking an exceptional Member of Technical Staff (MTS) focused on ML Product. This is a high-ownership role crucial for scaling their platform to millions of documents, requiring strong fundamental understanding of how to build, measure, and iterate on commercial ML systems for the enterprise. What You’ll Be Doing • Build the core ML and product infrastructure powering products for tax professionals, utilizing foundational models., • Rapidly improve core metrics by iterating on the dataset strategy, inference systems, and internal tax logic., • Engage directly with accountants and tax professionals to understand needs and build a scalable, high-quality, and accurate product that drives adoption., • Integrate the inference pipeline into an end-to-end product that transforms accounting workflows., • 4+ years of experience in Machine Learning Engineering, with a strong focus on creating end-user value (rather than just model fine-tuning)., • 5+ years of experience working with commercial ML systems in a meaningful ownership role., • Strong fundamental understanding of how to build, measure, and iterate on ML-powered enterprise or consumer products., • Salary: $200K - $325K, • Equity: Stock options also included, • Visa Sponsorship: Available Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search. Commitment to Equality and Accessibility: At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing . MLabs Ltd collects and processes the personal information you provide such as your contact details, work history, resume, and other relevant data for recruitment purposes only. This information is managed securely in accordance with MLabs Ltd’s Privacy Policy and Information Security Policy, and in compliance with applicable data protection laws. Your data may be shared only with clients and trusted partners where necessary for recruitment purposes. You may request the deletion of your data or withdraw your consent at any time by contacting .

Job Description Embark on a transformative journey at the forefront of innovation as a Generative AI Strategist. Are you ready to shape the future of business by unleashing the power of generative AI and machine learning? Join us in driving strategic alignment, fostering collaborative engagement, and leading sales initiatives to deliver tangible business value through cutting-edge generative AI solutions. If you possess a passion for innovation and a drive to revolutionize businesses through generative AI, we welcome you to be part of our dynamic team. Seize this opportunity to drive impactful change and lead businesses into a new era of technological advancement as a Generative AI Strategist. Key Responsibilities: Strategic Alignment: • Facilitate alignment between the customer's technologists and business leaders to unleash the potential of generative AI and machine learning for driving business value., • Work closely with various teams within the customer's organization, including applied scientists, solutions architects, business development, marketing, and industry specialists to foster collaboration and innovation., • Lead the strategic direction of large, complex sales opportunities from inception to successful closure and delivery., • Conduct interactive workshop sessions with customers to identify potential areas for deploying generative AI and machine learning solutions., • Proven experience in strategizing and implementing generative AI solutions in a business context., • Strong communication skills to engage with stakeholders at all levels and effectively convey complex concepts., • Expertise in collaborating with cross-functional teams and external partners to drive innovation and business growth., • Demonstrated ability to lead sales processes for complex technological solutions.

Job Description Location: San Francisco, CA Employment Type: Full-time Work Arrangement: On-site (minimum 3 days per week) About the Role Our client, a venture-backed company aiming to revolutionize the networking industry by creating a vertically integrated infrastructure provider, is seeking a Model Engineer to join their founding core AI team. This is a high-impact role focused on transforming a market with hundreds of billions in revenue by applying cutting-edge machine learning to internet infrastructure. You will be responsible for the full lifecycle of model development, from data to production deployment, and will directly collaborate with founders to define technical vision and team culture. What You'll Do • Train end-to-end models for fault prediction, network state modeling, and autonomous repair., • Build multi-modal models over structured networking data, implementing function-calling for network decisions., • Evaluate model performance over real-world hardware and virtualized environments., • Ship models into production networks, collaborating closely with firmware and application teams., • 2+ years of post-academic experience in model development., • Experience building, training, and scaling neural networks from the ground up., • Strong background in Python and ML coding (PyTorch)., • Comfortable with the full model lifecycle, including data cleaning, pipeline building, evaluation, and fine-tuning., • Bonus points: Experience training large language models (LLMs) and/or an entrepreneurial background (founding a startup)., • Salary: $200K - $300K (Base salary)., • Equity: Significant equity designed to be highly competitive. At the current Series C valuation of $1.2 billion, the initial grant is designed to be worth approximately $200K$-$300$K annually, with potential for substantial growth ($10$-$-15$x multiples projected over four years)., • Total Compensation: Highly competitive, with flexibility to adjust the cash/equity split. There is no strict cap for exceptional talent., • Visa Sponsorship: Available and facilitated by a dedicated law firm., • Work Policy: On-site in the San Francisco office (minimum three days a week). Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search. About MLabs MLabs is a full-stack software consultancy working with leading blockchain, AI, and tech startups worldwide. We’re supporting this client with their hiring, and you’ll be joining their team directly. ???? Apply now to be part of one of the most exciting AI startups in San Francisco. Commitment to Equality and Accessibility: At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing . MLabs Ltd collects and processes the personal information you provide such as your contact details, work history, resume, and other relevant data for recruitment purposes only. This information is managed securely in accordance with MLabs Ltd’s Privacy Policy and Information Security Policy, and in compliance with applicable data protection laws. Your data may be shared only with clients and trusted partners where necessary for recruitment purposes. You may request the deletion of your data or withdraw your consent at any time by contacting .

We’re looking for a Machine Learning Engineer who will build out and design machine learning infrastructure for a team of data & remote sensing scientists, working collaboratively with the Analytics and Software teams to deliver data-driven products and solutions. Your role as Machine Learning Eng

If you're passionate about applying cutting-edge machine learning in a high-stakes domain, we’d love to meet you. As a Machine Learning Engineer at Latent, you’ll design and deploy advanced models at the frontier of medical language understanding. Neurodivergence, for example, attention-deficit/

Machine Learning Engineer - Fine Tuning. As a Machine Learning Engineer specializing in Fine-Tuning at Baseten, you'll create value by leveraging our infrastructure to fine-tune large language models and other modalities, working directly with customers to meet their goals. Inclusive culture fosteri

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The project scientist will make significant and creative contributions in the area of machine learning & data analytics. These positions will work with a dedicated team to develop data analytics software in terabyte- to petabyte-scale imaging projects.

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Machine Learning Engineering Lead. Machine Learning Engineering Lead.

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Computer Science, Machine Learning, Robotics, or a related field - or equivalent practical experience. We’re looking for a Principal Machine Learning Engineer to lead the development of these foundational AI systems within the Unity engine, empowering creators to build smarter, more responsive in-

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Atlassians can choose where they work — whether in an office, from home, or a combination of the two.That way, Atlassians have more control over supporting their family, personal goals, and other priorities.We can hire people in any country where we have a legal entity.Interviews and onboarding ar

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