Senior Machine Learning Engineer - Generative AI Platform

Join Databricks Mosaic AI as a Senior Machine Learning Engineer and take the lead in developing our cutting-edge generative AI platform. Our team, formed in late 2020, empowers businesses by allowing them to securely fine-tune, train, and deploy custom AI models using their own data. This ensures maximum security and control while being compatible with all major cloud providers, allowing for unparalleled flexibility in AI development.Since our integration into Databricks in July 2023, we have been dedicated to tackling some of the world's most challenging problems, from revolutionizing transportation to accelerating medical advancements. We leverage deep data insights to enhance our customers' business capabilities and thrive on overcoming technical challenges to deliver superior data and AI solutions.Role Overview:As a Senior Machine Learning Engineer, you will play a pivotal role in the design and implementation of our generative AI platform, covering the entire ML development lifecycle, including data generation, training, evaluation, serving, and agent-building. Your expertise will be essential in translating user requirements into intuitive product interfaces while constructing robust backend distributed systems that drive these features.

About FaireFaire is a transformative online wholesale marketplace, driven by the conviction that local businesses are the future. Independent retailers around the globe generate more revenue than massive corporations like Walmart and Amazon combined, yet individually, they remain small. At Faire, we harness technology, data, and machine learning to connect this vibrant community of entrepreneurs. Think of your favorite local boutique — we empower them to discover and sell the best products from around the world. With our innovative tools and insights, we aim to level the playing field, enabling small businesses to thrive against larger competitors.By championing the growth of independent businesses, Faire positively impacts local economies on a global scale. We’re in search of intelligent, resourceful, and passionate individuals to join us in fueling the shop local movement. If you value community, we invite you to be part of ours.About this RoleAs the Senior Staff Machine Learning Platform Engineer, you will spearhead the technical vision and evolution of Faire's ML platform. You will establish standards, influence organization-wide architecture, and lead intricate, cross-functional initiatives that enhance data science velocity at scale. This position is crucial for adapting ML workflows to leverage modern AI productivity tools. You will not only develop models but also design the systems that enable those models to empower tens of thousands of small retailers in competing and growing their local businesses.

About Us:At Ambience Healthcare, we are not just another scribe; we are pioneering an AI intelligence platform that reinvigorates the human touch in healthcare while delivering significant ROI for health systems nationwide.Our innovative technology enables healthcare providers to concentrate on delivering exceptional care by alleviating the administrative burdens that detract from patient interactions and their most impactful work. Ambience provides real-time, coding-aware documentation and clinical workflow support in ambulatory, emergency, and inpatient settings across leading health systems in North America.Our team is driven by a relentless pursuit of excellence and extreme ownership, dedicated to crafting the best solutions for our health system partners. We champion transparency, positivity, and thoughtful engagement, holding each other accountable because we understand the significance of the challenges we tackle.Ambience has earned accolades such as being ranked #1 for Improving the Clinician Experience in the KLAS Research Emerging Solutions Top 20 Report, being recognized by Fast Company as one of the Next Big Things in Tech, and being named one of the best AI companies in healthcare by Inc. We were also selected as a LinkedIn Top Startup in 2024 and 2025. Our esteemed investors include Oak HC/FT, Andreessen Horowitz (a16z), OpenAI Startup Fund, and Kleiner Perkins — and our journey is just beginning.The Role:As a Staff Machine Learning Engineer, you will play a crucial role in advancing clinical AI that impacts millions of patient encounters across the largest health systems in the nation. Your contributions will directly influence the speed at which we enhance our AI capabilities through the platform you will oversee.You will design and implement evaluation and release processes that empower teams to deliver with confidence, create observability tools to identify quality issues pro-actively, and develop debugging tools that facilitate rapid issue reproduction. Additionally, you’ll work on the chart context retrieval layer that transforms patient history into model-ready inputs.Our goal is to enable teams to iterate on quality within days, not weeks, ensuring that every enhancement you implement adds value across all product teams each quarter.Please note that our engineering roles operate in a hybrid model from our San Francisco office (3 days per week).What You’ll Own:Evaluation & Release Infrastructure — Developing automated grading systems and release gates that function seamlessly across product teams, creating a unified evaluation dataset with version control to replace fragmented workflows. Implementing production-quality monitoring that includes end-to-end tracing, shared metrics, and automated alerts.Debugging Tools — Building encounter replay features that reconstruct precise inference inputs (including retrieved chart context, packed prompts, and model versions) to allow teams to troubleshoot issues without sifting through logs. Creating differential views to compare known good states with regressions.

Be a Part of the Revolution in E-Commerce with Whatnot!Whatnot stands as the leading live shopping platform across North America and Europe, where you can buy, sell, and explore the items you cherish. We are transforming the landscape of e-commerce by merging community engagement, shopping, and entertainment into a unique experience tailored just for you. As a remote-first team, we are driven by innovation and firmly rooted in our core values. With operational hubs in the US, UK, Germany, Ireland, and Poland, we are collaboratively crafting the future of online marketplaces.From fashion and beauty to electronics and collectibles like trading cards, comic books, and live plants, our live auctions cater to a diverse audience.And this is just the beginning! As one of the fastest-growing marketplaces, we are on the lookout for innovative, forward-thinking problem solvers in all areas of our business. Stay updated with the latest from Whatnot through our news and engineering blogs, and join us in empowering individuals to transform their passions into successful ventures while fostering community through commerce. The RoleWe are seeking passionate builders—intellectually curious, entrepreneurial engineers who are ready to pioneer the future of AI and ML at Whatnot. You will be responsible for designing and scaling the foundational infrastructure that supports machine learning and self-hosted large language model applications throughout the organization. Collaborating closely with machine learning scientists, you will facilitate the deployment of cutting-edge models into production, creating entirely new product experiences. Your work will involve constructing systems that ensure advanced machine learning is reliable and efficient at scale—from low-latency model serving to distributed training and high-throughput GPU inference.Your Responsibilities:Lead the infrastructure that powers AI and ML models across vital business domains—enhancing growth, trust and safety, fraud detection, seller tools, and more.Prototype, deploy, and operationalize innovative ML architectures that significantly influence user experience and marketplace dynamics.Design and scale inference infrastructure capable of managing large models with minimal latency and maximal throughput.Construct distributed training and inference pipelines utilizing GPUs, as well as model and data parallelism.Push the boundaries of your expertise and explore new technologies and methodologies.

Saris AI develops applied AI solutions for the banking sector, with teams in San Francisco, Montreal, and Toronto. The company builds automation tools that handle complex, long-context reasoning and agent-driven decision-making. Reliability and compliance shape every product, and Saris AI's agents already manage real customer workflows in production. As revenue grows, the engineering team is expanding to enhance current offerings and explore new directions. The Senior Machine Learning Engineer role is based in San Francisco and sits within the core engineering group. The team works in a collaborative, early-stage setting, balancing infrastructure needs with the delivery of features that serve customers directly. What you will do Build and maintain machine learning infrastructure, such as evaluation frameworks, prompt management systems, and tools for model observability. Develop new AI features for customers while supporting and improving the underlying infrastructure. Shape strategies for evaluation, LLM routing, prompt engineering, and model selection. Set practical standards to boost quality without slowing down development. Guide technical direction by clarifying trade-offs and architectural choices. Requirements Minimum 4 years of experience in machine learning or AI engineering, including production deployment of ML systems. Direct experience with large language models, prompt engineering, evaluation techniques, and model routing. Background in building tools and systems that deliver value to users. Comfort making pragmatic trade-offs and recognizing when a solution is sufficient. Ability to navigate ambiguity, define problems, and deliver results independently. Strong focus on end users and understanding the impact of ML decisions on customer experience. Supports team growth through code reviews, collaboration, and clear technical communication. Bonus Experience in regulated industries, especially banking.

About This Role Join Scale AI's Applied ML team as a Machine Learning Research Engineer, focusing on the development of advanced data infrastructure for leading agentic large language models (LLMs) such as ChatGPT, Gemini, and Llama. You will be responsible for architecting scalable multi-agent systems aimed at validating agentic reasoning and behaviors, enhancing human expertise, and conducting research to address real-world agent reliability failures, even in the face of strong benchmarks. Your contributions will directly impact the deployment of production fixes. This role is ideal for exceptional engineers who possess a deep research rigor and a strong commitment to creating practical, high-impact systems. You will iterate rapidly using data, leverage AI tools for accelerated development, and collaborate closely with engineering, product, and research teams. If you have a knack for transforming cutting-edge agent research into dependable deployed systems, we would love to hear from you.

Join us in creating the backbone of data infrastructure for real-world robotic operations.As robotics transitions from research labs to real-world applications across factories, warehouses, vehicles, and field deployments, understanding the intricacies of robotic performance becomes critical. When robots encounter failures or unexpected behaviors, data analysis is key to deciphering the underlying issues.At Foxglove, we are at the forefront of building tools for observability, visualization, and data infrastructure that empower robotics and autonomous systems teams to manage, analyze, and derive insights from vast amounts of multimodal sensor data collected from operational systems and production fleets.Role OverviewWe are seeking a passionate ML Platform Engineer with robust infrastructure expertise to design, deploy, and scale our data platform systems. This platform-centric role will allow you to take charge of the infrastructure layer that facilitates machine learning in production environments, going beyond just the models themselves.Your responsibilities will encompass ensuring the reliability, scalability, and performance of the ML platform, including areas such as inference serving, pipeline orchestration, training infrastructure, and evaluation frameworks. You will be tackling substantial challenges such as managing petabyte-scale multimodal robotics data and optimizing high-throughput retrieval and embedding pipelines in a hands-on infrastructure capacity.Key ResponsibilitiesDesign and operationalize production inference infrastructure, focusing on model serving, autoscaling, load balancing, and cost efficiency across cloud environments.Own the platform architecture for embedding and retrieval pipelines that enable semantic search across multimodal robotics data (image, video, point cloud, and time series).Develop and sustain the training and evaluation infrastructure that supports rapid model performance iteration, including job orchestration, experiment tracking, and dataset versioning.Lead decisions on cloud infrastructure (AWS/GCP) that affect latency, throughput, reliability, and scalability.Establish platform abstractions and internal tools that empower product engineers to deliver ML-enhanced features without managing infrastructure directly.Assess, integrate, and operationalize third-party ML infrastructure components while establishing clear build vs. buy frameworks for the team.

tvScientific, powered by Pinterest, develops a connected TV (CTV) advertising platform designed for performance marketers. The platform combines media buying, optimization, measurement, and attribution to automate and improve TV advertising. Built by professionals in programmatic advertising, digital media, and ad verification, tvScientific aims to deliver measurable results for advertisers. Role overview As a Machine Learning Platform Engineer, you will join a team that operates where Site Reliability Engineering meets low-latency distributed systems. This team advances Pinterest’s real-time machine learning and measurement infrastructure, focusing on sub-millisecond decision-making and high-throughput data access. Seamless integration with Pinterest’s core stack is central to the work. What you will do Design and build systems to keep queries and RPCs fast and reliable, even during periods of heavy demand. Develop and enhance the foundation of the machine learning training and serving stack. Address challenges in storage, indexing, streaming, fan-out, and managing backpressure and failures across services and regions. Collaborate with software engineering, data infrastructure, and SRE teams to ensure systems are observable, debuggable, and ready for production. Key areas of focus I/O scheduling and batching Lock-free or low-contention data structures Connection pooling and query planning Kernel and network tuning On-disk layout and indexing strategies Circuit-breaking and autoscaling Incident response and failure management NixOS Defining and maintaining SLIs and SLOs This position is a strong fit for engineers interested in building and operating large-scale infrastructure, particularly those who enjoy working on real-time systems, observability, and reliability.

At Scale AI, we are at the forefront of the AI revolution, providing the essential data infrastructure that empowers organizations to create and implement robust AI applications. Our partnerships with top enterprises and government entities accelerate their AI goals through innovative data annotation platforms, generative AI solutions, and comprehensive enterprise AI capabilities.Discover the General Agents TeamThe General Agents team, an integral part of Scale's Enterprise division, is dedicated to developing advanced general agents tailored for diverse customer applications. We operate at the cutting edge of agent technology, transforming sophisticated reasoning and agentic capabilities into dependable, production-ready systems that deliver substantial economic benefits. Our agents are designed for scalability, focusing on recurring enterprise challenges, with a strong emphasis on generalization, extensibility, and widespread deployment.Your Impact in This RoleAs a Senior/Staff Machine Learning Engineer on the General Agents team, you will be pivotal in architecting, building, and deploying production-grade AI agents that address significant enterprise challenges. Your role will encompass the entire agent lifecycle—from system design and model evaluation to deployment and iterative refinement—effectively merging cutting-edge agent techniques with the practicalities of real-world customer settings.You will:Create and implement comprehensive agent systems that integrate LLM reasoning, memory, tool usage, and control logic to tackle recurring enterprise challenges.Develop scalable and reliable agent architectures that can adapt to a variety of customer data and tools.Establish evaluation frameworks, datasets, environments, and metrics to assess agent performance, reliability, and business outcomes in live settings.Collaborate with product managers, clients, data annotators, and engineering teams to translate enterprise needs into robust agent designs.Transition cutting-edge agent techniques (e.g., planning, multi-step reasoning, tool utilization, multi-agent collaboration) into maintainable and observable systems.Oversee the deployment, monitoring, and iterative enhancement of agent systems, including failure analysis and continuous improvement based on actual usage.Guide the technical direction and architectural practices for general agent development, with increased scope and leadership at the Staff level.

Join Whatnot as a Machine Learning Platform Engineer, where you'll play a pivotal role in shaping the future of our AI-driven solutions. In this dynamic position, you will collaborate with cross-functional teams to design, implement, and optimize machine learning platforms that drive efficiency and innovation.Your expertise will be critical in enhancing our data processing capabilities and deploying robust machine learning models at scale. If you are passionate about leveraging cutting-edge technology to solve complex challenges, we want to hear from you!

About the RoleHinge Health is a leading digital health company dedicated to delivering innovative, evidence-based solutions for musculoskeletal (MSK) pain management. Our unique approach combines personalized exercise therapy with virtual care, empowering individuals to effectively manage chronic pain and enhance their quality of life, all while reducing healthcare costs. By partnering with employers and health plans, we aim to scale our solutions and improve overall employee health and productivity.Join our dynamic AI platform team at Hinge Health, where we are at the forefront of revolutionizing how businesses harness the power of Artificial Intelligence. We are searching for a Senior Software Engineer with a robust background in software engineering and a passion for AI to contribute to our mission.As a Senior Software Engineer, you will play a crucial role in developing and maintaining vital components of our AI infrastructure. You will collaborate closely with engineers and data scientists to ensure the platform effectively supports the intricate needs of AI models and machine learning workflows.Our team thrives in a continuous deployment DevOps culture, taking pride in maintaining high standards of code in production. Our production systems leverage technologies such as React Native, React, Node.js, TypeScript, Python, Nestjs, GraphQL, Docker, AWS, Postgres, Redis, Apollo, and Redux. We follow a trunk-based CI/CD workflow and uphold the highest security and compliance standards, including HIPAA, HITRUST, SOC 2, and CCPA.What You'll AccomplishCollaborate with the AI/ML team to effectively integrate models and agents into the platform, ensuring seamless deployment.Write clean, maintainable code with a focus on performance, reliability, and scalability.Develop and sustain APIs and microservices that facilitate AI model and agent deployment and data processing.Troubleshoot and resolve platform performance, integration, and reliability issues.Work alongside cross-functional teams to gather technical requirements and deliver efficient solutions.Contribute to ongoing improvements in the AI platform’s systems and workflows, providing ideas and feedback during architectural discussions.Hinge Health Hybrid ModelWe recognize that both remote and in-person work offer unique benefits, and we aim to capitalize on the strengths of both approaches. Employees in hybrid roles enjoy the flexibility of working from home while also engaging in person as needed.

Quizlet, Inc. supports millions of learners each month by combining cognitive science with advanced machine learning. The platform serves two-thirds of U.S. high school students and half of college students, powering over 2 billion learning interactions monthly. Quizlet’s mission centers on making education more personal and effective for students, professionals, and lifelong learners. The AI & Data Platform team underpins Quizlet’s applied AI initiatives. This group develops and maintains the systems behind personalization, recommendations, the AI Coach, content generation, and emerging agentic experiences. The team oversees the full machine learning model lifecycle: data and feature engineering, training, evaluation, deployment, and inference. Reliability, speed, security, and observability guide their work. Their approach blends managed Google Cloud services, top vendor tools, open-source solutions, and custom internal abstractions to achieve efficient, reliable outcomes. Role overview The Senior Staff Engineer, AI Platform, is a senior individual contributor who defines the technical direction for Quizlet’s next generation of machine learning and large language model infrastructure. This hands-on role involves architecting core platform systems, steering build-versus-buy decisions, and collaborating with teams across Applied AI, Data Science, Product Engineering, and Infrastructure. The position sets standards for how models and LLM-driven systems are trained, evaluated, deployed, and governed at scale. This role is well suited to an engineer who excels at the senior-staff level in large organizations but values the autonomy and impact of a smaller, cloud-native setting. The technology stack includes Google Cloud, Kubernetes and GKE, distributed training, MLflow workflows, data and feature platforms, online and asynchronous inference, and the evaluation and observability tools needed to operate predictive ML and LLM systems at scale. Work location and schedule This is an onsite position based in San Francisco, CA. Team members are expected in the office at least three days a week: Monday, Wednesday, and Thursday, to foster collaboration.

Airbnb began in 2007 with two hosts and three guests in San Francisco. Since then, the platform has grown to over 5 million hosts and more than 2 billion guests worldwide. Airbnb connects people with unique places to stay and experiences, building authentic community connections across nearly every country. The team: Growth Platform Engineering The Growth Platform team focuses on driving sustainable, long-term growth for Airbnb. The team’s mission centers on building an agentic system and supporting capabilities to help all Airbnb offerings grow, both now and in the future. Efforts include delivering personalized and relevant content and product experiences to users, both on and off the Airbnb platform. The team is working toward a future where AI identifies opportunities, creates campaigns, personalizes experiences, and optimizes outcomes with minimal human input. This journey moves through a maturity curve: AI-assisted, agentic, and ultimately autonomous systems, always with human oversight to ensure brand safety, quality, and compliance. Growth Platform Engineering is tightly integrated with the Airbnb product, enhancing the customer journey and enabling new ways for users to engage. The platform supports a range of digital marketing channels, landing pages, email, push notifications, SMS, and digital advertising, as well as the machine learning and data infrastructure that powers these efforts. What you will do Develop AI-driven solutions to shape the future of Airbnb’s agentic growth platform, using the latest AI methodologies. Lead and mentor engineers through brainstorming, design, and implementation of AI products and features, from initial concept to deployment. Work at the intersection of technical depth, architectural innovation, and mentorship as a Senior Staff Engineer. Collaborate with cross-functional teams to build scalable systems that operate globally. Help evolve the foundational elements of Airbnb’s AI-powered growth systems.

Artificial Intelligence (AI) is becoming increasingly crucial across all sectors of society. At Scale AI, our mission is to expedite the advancement of AI applications. With nine years of experience, we have established ourselves as the leading AI data foundry, facilitating groundbreaking developments in AI, including generative AI, defense applications, and autonomous vehicles. Following our recent investment from Meta, we are committed to enhancing our capabilities by developing cutting-edge post-training algorithms that are essential for optimizing complex agents in enterprises globally.The Enterprise ML Research Lab is at the forefront of this AI revolution. We are dedicated to crafting a suite of proprietary research tools and resources that cater to all of our enterprise clients. As a Machine Learning Research Engineer focusing on Agents, you will apply our Agent Reinforcement Learning (RL) training and building algorithms to real-world enterprise datasets across our clients and benchmarks. Your role will involve developing top-tier Agents that achieve state-of-the-art results through a blend of post-training and agent-building algorithms.If you are passionate about influencing the trajectory of the modern Generative AI movement, we would love to hear from you!

Saris AI, based in San Francisco with teams in Montreal and Toronto, develops advanced agentic AI systems for the banking industry. The company focuses on automating complex workflows that require long-context reasoning, integration with legacy systems, and strict compliance. With live AI agents already supporting real customer operations, Saris AI is expanding quickly and seeking technical leaders who want to shape the future of work in banking. Role overview This is a hands-on leadership position within the core engineering team in San Francisco. The Machine Learning Engineering Lead will guide machine learning systems from initial concept through scaling, helping define both the technical vision and the supporting infrastructure. What you will do Oversee the ML/AI function end to end, setting technical direction and standards across the company. Design and supervise development of multi-modal, agentic AI systems that power live customer workflows. Build and manage evaluation frameworks, datasets, and metrics to improve agent performance. Drive productionization of ML systems with an emphasis on reliability, scalability, and compliance. Recruit, develop, and mentor a high-performing ML team, fostering strong practices in modeling, experimentation, and deployment. Requirements 8+ years of experience in machine learning or AI engineering, including time as a technical lead or manager. Proven track record leading ML projects from concept to production deployment. Expertise with large language models (LLMs) and/or agentic systems, especially in customer-facing products. Strong grasp of ML fundamentals: deep learning, transformers, model evaluation, and trade-offs. Hands-on experience scaling ML systems in production, with a focus on monitoring, iteration, and reliability. Ability to lead engineering teams, influence architecture, and set technical direction. Comfort working in early-stage, ambiguous, and rapidly changing environments.

Join Affinity as a Senior Machine Learning Engineer to shape the future of our AI Platform. In this role, you will leverage your expertise in machine learning to develop scalable solutions that drive innovation and enhance our platform's capabilities. Collaborate with cross-functional teams to implement advanced algorithms, optimize performance, and contribute to impactful projects that redefine industry standards.

Join Our Team as a Machine Learning EngineerSaris-AI is a pioneering applied AI startup, based in San Francisco and Montreal, focused on revolutionizing the banking sector. Our mission is to address a colossal $100 billion/year challenge that is rapidly expanding, innovating the limits of what can be achieved with advanced multi-turn AI systems.We aim to automate complex workflows that necessitate long-context reasoning, orchestration of tools across legacy systems, and rigorous compliance processes—solving problems that currently lack definitive solutions.Our team has successfully deployed AI agents that manage real customer workflows effectively in production. As we expand our customer base and accelerate our growth, we are in search of highly skilled technical builders who aspire to make a significant impact in the early stages of our journey.As a foundational Machine Learning Engineer, you will own our entire ML stack and bring custom agents to life.

About UsAt Citizen Health, we believe that the right advocate can significantly enhance healthcare experiences and outcomes. Founded on the principles of personal healthcare journeys, we leverage a unique combination of data, artificial intelligence, and community engagement to craft a personalized AI advocate. Our platform harnesses patients' comprehensive medical histories alongside data from a vast network of individuals, providing tailored insights for effective clinical decisions and everyday challenges. We focus initially on rare and complex conditions, allowing patients to share their information for mutual benefit, while empowering biopharma and researchers with regulatory-grade data that accelerates the drug development process for critical treatments.Our team consists of seasoned entrepreneurs with successful track records, backed by esteemed investors such as 8VC, Transformation Capital, and Headline Ventures. We are passionate about reshaping the future of consumer healthcare.Position OverviewCitizen Health is on the lookout for talented AI/Machine Learning Engineers to spearhead the development and implementation of innovative AI solutions for our patient-centered platform. This pivotal role involves crafting and deploying advanced machine learning models that convert intricate health data into actionable insights for patients, healthcare professionals, and researchers.As a vital technical leader, you will be at the cutting edge of applying sophisticated machine learning methodologies to tackle complex challenges in rare disease research and patient care. Your contributions will be crucial in developing AI-driven solutions that enhance disease comprehension, treatment options, and overall patient outcomes.Key ResponsibilitiesDesign and execute comprehensive machine learning solutions, covering data preprocessing to model deployment and ongoing monitoring.Develop and refine advanced Large Language Models (LLMs) tailored for healthcare applications, utilizing techniques such as fine-tuning and Retrieval-Augmented Generation (RAG).Construct robust data pipelines for validation and deployment processes.Implement machine learning systems capable of processing and analyzing diverse healthcare data types, including structured clinical data, medical imaging, and unstructured text.Collaborate closely with backend engineers to seamlessly integrate ML models into our production infrastructure.Ensure that ML systems adhere to rigorous healthcare compliance standards while maintaining optimal performance.

Innovate Boldly. Shape Tomorrow. Our VisionCrafting everyday AGI. Reliable, consumer-friendly agents that transform human-AI synergy for millions. Our software is designed to act as a collaborator, enhancing your daily capabilities.Why Choose AGI, Inc.?We are a discreet collective of exceptional founders and AI pioneers, whose expertise spans Stanford, OpenAI, and DeepMind. Our team leads the way in mobile and computer-based agents, scaling these innovations for consumer use.With a foundation rooted in extensive research on agents, our AI prioritizes trustworthiness and reliability as fundamental principles.Backed by top-tier investors who previously supported the first wave of AI leaders, we are now positioned to create the next generation: everyday AGI. (Check out the demo)If you envision possibilities where others perceive restrictions, continue reading.Your RoleTraining Automation: Design and execute robust CI/CD pipelines tailored for machine learning workflows. Automate nightly and on-demand training sessions encompassing data ingestion, job orchestration, checkpointing, and artifact management, with a focus on reliability.Evaluation Infrastructure: Develop scalable evaluation frameworks that automatically benchmark models with each merge. Enhance latency and resource efficiency to ensure quick experimentation and immediate detection of performance regressions.Research Tooling: Create internal SDKs, CLIs, and lightweight UIs (e.g., Streamlit, Retool) empowering researchers to:Examine trajectories and tracesVisualize model failuresOrganize and oversee datasetsIterate seamlesslyYou'll facilitate a user-friendly experimentation process.Observability & Performance: Enforce comprehensive tracking for:Model latency, throughput, and error ratesGPU utilization, and more.

Are you ready to push the boundaries of what you believe you're capable of? At Coinbase, our vision is to enhance economic freedom globally. This is a grand, ambitious endeavor that challenges us to deliver our best every day as we construct the foundational onchain platform and shape the future of the global financial system.To drive our mission forward, we are in search of a unique candidate. We seek an individual who is not only passionate about our objective but also believes in the transformative power of cryptocurrency and blockchain technology to revolutionize the financial landscape. We are looking for someone eager to make a significant impact, who thrives under pressure while collaborating with a team of highly skilled professionals, and who actively seeks constructive feedback for continuous improvement. We want a problem-solver who embraces challenges head-on.Our work culture is intense and not suited for everyone. However, if you aspire to build the future alongside exceptional individuals and are ready to meet high expectations, this is the place for you.While many positions at Coinbase are remote-first, we are not solely remote. In-person engagements are expected throughout the year. We conduct team and company-wide offsites several times a year to promote collaboration, connection, and alignment. Your attendance is both expected and fully supported.We are looking for a Senior Machine Learning Platform Engineer to join our Machine Learning Platform team. This team is responsible for developing the core components for feature engineering, as well as training and serving ML models at Coinbase. Our platform plays a crucial role in combating fraud, personalizing user experiences, and analyzing blockchains. You will have the opportunity to leverage your engineering expertise across various aspects of large-scale ML development, including stream processing, distributed training, and highly available online services.