Staff Senior Machine Learning Scientist Jobs

Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in large-scale Foundation models, VLMs, and VLAs to make autonomous driving as seamless as possible. The Opportunity Are you excited to drive our ML Performance Optimization initiatives and make our ML models that enable autonomous driving as fast and efficient as possible? You will get to work with SOTA accelerators, cutting-edge techniques in distributed training, quantization, distillation, and pruning, among other things, working closely with all the Autonomy teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox. We build and operate the base layer of ML tools, model development, and serving systems that our applied research teams use for in- and off-vehicle ML use cases. You will work alongside a team of strong software engineers and act as a force multiplier for our internal customers. This team has many growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look here. If you want to learn more about our ML Infrastructure, here is one of our past talks at re:Invent. In this role, you will: Lead the design, implementation, and operation of training performance optimizations (data/tensor/pipeline parallelism, mixed precision, gradient checkpointing, GPU kern

Zoox is developing fully autonomous vehicles and the supporting ecosystem required to bring the technology to market at scale. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We believe the transition to self-driving vehicles requires a combination of elegant vision and uncompromising execution. As a Staff Closures Engineer, you will own the closures architecture for the vehicle. You will be the subject matter expert for how doors, latches, hinges, actuators, seals, and glazing behave as a system, how that system interacts with the rest of the vehicle, and where the interdependencies between it and body, EE, firmware, manufacturing, and service will surface later in the program. This is a hands-on architecture role, not a detached one: alongside setting system direction, you will personally own a set of the most difficult parts in the system and take them from concept through sourcing, validation, and launch. Our closures are unlike conventional vehicles. They are fully automated, operate at a duty cycle closer to transit than to passenger cars, carry sensor and compute integration, and have no driver to compensate for them. The person in this role is comfortable being accountable for both the architecture and the specification. In this role, you will: Serve as the technical owner and subject matter expert for the complete closures system. Understand how every component interfaces within the system and with the rest of the vehicle, and anticipate interdependencies between closures and adjacent complex systems before they become integration failures. Set and defend the closures architecture across current and future vehicle programs - mechanism topology, load paths, sealing and water-management strategy, actuation and state-detection strategy, tolerance and dimensional strategy, and the hardware/firmware boundary - making the trade-offs explic

Zoox is seeking a Senior / Staff Technical Program Manager, Change Governance to own the end-to-end orchestration of product changes as they move from tentative engineering approval through cross-functional review to implementation on the production line. This role sits at the center of a multidisciplinary process, ensuring every change is tracked, properly vetted, and executed with full governance and traceability at each stage. In this job, you will Serve as the single point of accountability for governance of a change from tentative Engineering approval through multidisciplinary alignment across Engineering, Manufacturing, Quality, Purchasing, Supply Chain, and Logistics to production-line implementation. Assess and manage how a change cascades through multi-tier supply chain dependencies, coordinating supplier qualification and launch-readiness requirements as needed Partner with production-line teams at Zoox and relevant change management functions at suppliers to plan and confirm implementation readiness: timing, resourcing, build sequencing, documentation, and training. Maintain accurate, audit-ready records of change status, approvals, and decisions in relevant change management, ERP, and PLM systems. Build and maintain reporting and dashboards on change pipeline health, using scripts (e.g., Python, Apps Script, VBA) or AI tools to automate recurring data retrieval and reporting across Excel, Google Sheets, and Jira. Own and continuously improve the governance framework and checklist — required approvals, documentation, and gate criteria — partnering with IT/business systems teams to implement process and tooling improvements. Qualifications Bachelor's degree in Mechanical, Electrical, Industrial, Manufacturing Engineering, or a closely related engineering discipline <l

About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About the Role Snorkel AI is hiring a Forward Deployed Engineer focused on Computer Use Agents to partner with leading AI labs and enterprises on their most critical agentic-AI initiatives. In this role, you will lead the technical execution of complex customer engagements involving agents that operate computers, browsers, and software environments to complete realistic, multi-step tasks. You will translate ambiguous product and model challenges into robust task environments, datasets, evaluators, and delivery plans that improve agent reliability and downstream performance. You will work across the full delivery lifecycle—from technical discovery and solution design through implementation, evaluation, and production delivery. You will also identify patterns across engagements and turn successful approaches into reusable capabilities, technical standards, and product improvements. Main Responsibilities Computer Use Agents, Data, and Evaluation Design and build task environments, datasets, and evaluation workflows for computer-using agents operating across browsers, desktop applications, terminals, and other software interfaces Translate customer goals, agent failure modes, and real-world workflows into representative, multi-step tasks with clear success criteria Develop data-generation, validation, and quality-assurance pipelines for multimodal and agentic training and evaluation data Build automated evaluators, checks, and measurement frameworks to asse

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role The ML Infrastructure team is responsible for building & improving the core infrastructure for autonomy teams at Nuro. In this role, you will work closely with teams across Nuro, to design, build and deploy core infrastructure components in machine learning model life cycle, to push the autonomous future forward. You will have an opportunity to work across the full stack of machine learning solutions - from designing robust and scalable model & data pipelines to building to deploying the optimized models on Nuro’s fleet of self-driving robots! About the Work Design and develop ML workflow pipelines to train, optimize, validate, and deploy Nuro autonomy models. Develop and maintain continuous testing and monitoring systems for core ML infrastructure components. Develop observability to track ML model lifecycles from data generation to on-road validation. Maintain an in-house ML inference platform to serv

The Role We are seeking a highly skilled and hands-on SoC Floorplan Lead to own the physical foundation of our next-generation AI and Data Center SoCs. In this critical role, you will be the bridge between architecture, logic design, and physical design. You will work hand-in-hand with Chip Architects and RTL Leads to influence micro-architecture and ensure the physical implementation achieves best-in-class Power, Performance, and Area (PPA). If you love solving complex spatial puzzles on advanced technology nodes, integrating sensitive analog components, and driving execution in a high-energy start-up environment, this is the role for you. Key Responsibilities Top-Level Floorplanning: Own the SoC-level floorplan from concept to tape-out for high-performance, large-scale AI/Data Center chips on advanced process nodes (e.g., 5nm, 3nm or below). Architecture & RTL Collaboration: Partner closely with Architecture and RTL teams to provide early physical feasibility feedback. Drive block partitioning, shape optimization, and data-flow planning to achieve the absolute best PPA. Bump & Package Co-Design: Lead bump planning and IO ring definition. Work with packaging teams on flip-chip/advanced packaging constraints, ensuring optimal signal escape and power delivery. Custom & Analog Routing: Manage the placement and custom routing strategies for critical Analog/Mixed-Signal (AMS) IPs, high-speed SerDes (PCIe, Ethernet, Memory interfaces), PLLs, and sensitive clock distributions. Power Delivery Network (PDN): Design and analyze the top-level power grid, ensuring robust power delivery for high-current AI workloads while minimizing IR drop. Pin Assignment & Feedthroughs: Manage macro placement, block-level pin assignments, and top-level feedthrough planning to optimize global timing and routing congestion. Methodology Development: Build and maintain scalable Floorplanning workflows and

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role The Autonomy ML Infrastructure team is responsible for building & improving the core infrastructure for autonomy teams at Nuro. In this role, you will work closely with teams across Nuro, to design, build and deploy core infrastructure components in machine learning model life cycle, to push the autonomous future forward. You will have an opportunity to work across the full stack of machine learning solutions - from designing robust and scalable model pipelines to building to deploying the optimized models on Nuro’s fleet of self-driving robots! About the Work Optimize Nuro’s autonomy stack with cutting-edge optimization techniques like quantization, distillation, and model compression. Work with autonomy engineers to optimize, validate, and deploy large language models. Develop and maintain a world-class model compiler framework, FTL . Write robust, high quality software to increase our confidence in our vehicle

Zoox is building fully autonomous vehicles designed from the ground up for robotaxi service — and as we scale toward launch, our engineering infrastructure has to scale with us. We're hiring a Staff Site Reliability Engineer to own source control at Zoox, serving as the technical lead for the platform that every engineer depends on daily. This is a hands-on lead role. You'll set the direction for our Git-based monorepo, drive a restructuring of our Source Code management strategy, build the tooling that improves reliability and developer workflows, and partner with platform, security, and product teams to make source control a strategic asset rather than a bottleneck. The ideal candidate leads by building — with deep expertise in monorepo management (branching strategies, code review workflows, access controls, CI/CD) and a track record of improving developer productivity through code, not just guidance. You take ownership, measure what matters, and have the technical credibility to make decisions stick. In this role, you will: Own the technical strategy and roadmap for source control at Zoox. Plan and execute a strategic effort to scale source code management at Zoox: scoping, design, implementation, cutover, and validation, in partnership with security, platform, and engineering teams. Build and operate monorepo scalability improvements across repo structure, branch strategy, code ownership, large-file handling, and CI integration — including the scripts, hooks, and automation that make them stick. Develop the guardrails and developer-facing tooling that reduce toil for SRE and product engineering alike, measured by build times, merge friction, and interrupt volume. Set the technical bar through code reviews, design proposals, and pairing — and serve as the hands-on authority for source control decisions across Zoox engineering Qualifications 5+ years operating GitH

Zoox is on an ambitious journey to develop a full-stack autonomous mobility solution for cities and safely deploy such a robotaxi solution. The System Design and Mission Assurance (SDMA) team plays a foundational role in the company's success, responsible for constructing the safety case and fail-operational design for our autonomous driving robots before public road deployment. As a Systems Engineer at Zoox, you will be working with cross functional teams including product, feature, operations, vehicle engineering, software, autonomy, and legal to design, develop, and deploy systems that enable and support safe autonomous driving. You are responsible for ensuring these systems are developed within a safety engineering process that results in end-to-end traceability and achievement of both system safety targets and product requirements. In this role, you will: Lead powertrain safety and fail-operational design and analysis covering high-voltage battery systems, charging, propulsion, and on-vehicle load management Architect vehicle-level safety concepts, focusing on fault tolerance, and fail-operational behaviors necessary for supporting autonomy and ensuring mission assurance on the vehicle’s powertrain functions Develop vehicle level safety concepts covering fault detection, and vehicle level reaction for ensuring the powertrain systems can achieve mission objectives under presence of faults Own the delivery of key work-products including hazard analysis risk assessment (HARA), fault tree analysis (FTA), functional safety concept, vehicle level safety requirements, safety clearance artifacts, and quantitative residual risk assessments Drive consensus across product, feature, operations, vehicle engineering, software, autonomy and legal teams to implement and release safety requirements Qualifications B.S. or higher degree in Automotive, Aerospace, Robotics, Computer Science, Electrical, Mechanical, or

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role As a Senior/Staff Software Engineer working on driving behavior verification, you are responsible for implementing metrics that evaluate the end-to-end behavior of the Nuro Driver. These metrics will be used to quantify the safety of the driving behavior in our target ODD. This requires prior experience with the development or verification of behavior planning/prediction systems for robots, and a collaborative nature to work closely with a variety of teams across Nuro: Systems, Onboard Software, Simulation, Product, and Operations. About the Work Develop and implement in Python generalizable metrics to verify the driving behavior of an autonomous vehicle. Leverage a combination of machine learning (ML) models and safety metrics from literature to evaluate the end-to-end driving behavior. Evaluate these metrics on a variety of tests: synthetic and log simulation, on-road logs, closed-course testing data, and third-party acc

Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in large-scale Foundation models, VLMs, and VLAs to make autonomous driving as seamless as possible. The Opportunity Are you excited to drive our ML Performance Optimization initiatives and make our ML models that enable autonomous driving as fast and efficient as possible? You will get to work with SOTA accelerators, cutting-edge techniques in distributed training, quantization, distillation, and pruning, among other things, working closely with all the Autonomy teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox. We build and operate the base layer of ML tools, model development, and serving systems that our applied research teams use for in- and off-vehicle ML use cases. You will work alongside a team of strong software engineers and act as a force multiplier for our internal customers. This team has many growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look here. If you want to learn more about our ML Infrastructure, here is one of our past talks at re:Invent. In this role, you will: Develop and execute a strategic vision for the ML Performance Optimization team to unlock ML innovation in autonomous driving and rider experience. Lead the design, implementation, and operation of cutting-edge ML Training OR Inference performance optimization techniques to scale our VLM, VLA, and Foundational models and deplo

Zoox's Robot Software Infrastructure team is seeking a passionate software engineer to help develop and advance the common performant operating system that powers several devices on our vehicle including Autonomy systems. This team develops platform-level software and services, including operating systems that enable complex, hardware-accelerated workloads critical for autonomous driving on automotive-grade hardware. We work closely with cross-functional teams—including developers, release management, hardware engineering, manufacturing and operations—to support vehicle development and deployment at scale. You'll have the opportunity to influence the next generation of our platform, hardware, and robotaxi. If you are excited to explore a broad problem space and are mindful of how components fit within a larger system, you may be a great fit! In this role, you will: Design, develop, and maintain the operating system platform that powers various on-bot devices and applications Architect and implement platform-level software to support robust and scalable robotics infrastructure Configure and manage embedded Linux build systems (e.g., Yocto) and bootloader processes (e.g., U-Boot) to ensure reliable system startup and maintenance Develop and optimize device drivers and kernel-space components using C, C++, or Rust to meet performance and reliability requirements Collaborate cross-functionally to support seamless integration and delivery of the OS platform, triage issues, support new hardware bring-up and manufacturing functions Qualifications 8+ years delivering production systems and software applications, 2+ years of delivering custom Embedded Linux operating systems Have a deep understanding of Linux, build systems like Yocto, and bootloaders like U

As a Technical Lead on Zoox's internal agentic platform, you will own end-to-end integration of a tool-centric agent runtime with external and internal agent clients, line of business backends, scheduled and interactive agent workloads, and cloud operations (Kubernetes, observability, secrets management). You will translate architecture and security intent into stable tool contracts, testable integration milestones, and repeatable releases, and you will be the primary engineer when issues sit at the boundary between product surfaces, platform services, and upstream systems. This role is platform and service integration for an agentic framework that mediates tools (discovery, invocation, policy, and telemetry). Success is measured by reliable tool call paths over HTTP, correct authentication and scoping, environment parity from dev through production, and clear ownership across partner engineering, security, and infrastructure teams. In this role, you will: Own and lead integration strategy and execution across hosted services, shared libraries, standardized tool protocols (e.g., JSON-RPC over HTTP), REST APIs, and diverse callers (vendor agents, consoles, automation workers). Drive cross-functional delivery with backend API teams, partner agent owners, security, SRE/platform, and program management, ensuring formal sign-off where required. Debug and root-cause complex failures using structured logs, distributed traces, metrics, and gateway/session-token behavior, documenting durable mitigations and runbooks. Define and review all integration artifacts (contracts, allowlists, registry config, environment matrices, and interface assumptions) that upstream and downstream teams implement against. Contribute to release gating by ensuring container image promotion, configuration/secrets posture, smoke path execution for high-traffic flows, and disciplined branching/tagging for production inte

About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About the Role Snorkel AI is hiring a Forward Deployed Engineer focused on Synthetic Data Generation to partner with leading AI labs and enterprises on their most critical AI initiatives. In this role, you will lead the technical execution of complex customer engagements where synthetic data is used to improve model training, evaluation, and performance. You will translate ambiguous model and data challenges into effective data strategies, build scalable generation and evaluation pipelines, and use experimentation to continuously improve data quality and downstream model outcomes. You will work across the full delivery lifecycle—from technical discovery and solution design through implementation, evaluation, and production delivery. You will also identify patterns across engagements and turn successful approaches into reusable capabilities, technical standards, and product improvements. Main Responsibilities Synthetic Data Generation & Evaluation Design and build scalable synthetic data generation, transformation, filtering, and evaluation pipelines for complex AI use cases Translate model objectives, failure modes, and data gaps into synthetic data strategies, experiments, and technical specifications Develop LLM- and ML-assisted workflows to generate high-quality training and evaluation datasets across targeted behaviors, domains, and edge cases Build automated evaluators, quality checks, and measurement frameworks to assess correctness, relevance

Zoox is looking for an experienced software engineer to work on large-scale simulation pipelines used to validate the behavior of the Zoox self-driving vehicle. These are data and GPU intensive workloads built on Ray.io and Kubernetes. Given the massive scale and criticality of these pipelines, ensuring their reliability and efficiency has a significant impact on the company's ability to safely and quickly iterate on autonomy development. We are a small, scrappy team within the larger Autonomy organization. Although this role primarily involves off-vehicle pipelines, you will work closely with engineers developing the on-vehicle algorithms and models in our autonomy stack. We stay close to the end users - autonomy engineers - and think about the end to end use case for these validation pipelines. This is a hands-on role with a high degree of independence and ownership. You will be expected to contribute towards the framework’s architecture, reliability, efficiency, and grow its capabilities to support new use cases. You should have a track record of keeping production systems running with high availability. Experience with robotics or autonomous systems is not required but an understanding of the robotic data lifecycle is preferred. In this role, you will: Improve the cost efficiency, reliability, and performance of our validation and simulation pipelines Create production-grade APIs, SDKs, and tools to enable a varied set of validations of autonomous behaviors Improve the ML training pipelines supporting the autonomous behavior org Qualifications Bachelor’s degree in Computer Science or related field and 8+ years of industry experience Experience optimizing large-scale distributed systems for cost and efficiency Experience with AWS or similar providers Proficiency with Python and familiarity with C++ Bonus Qu