Fleet Associate Jobs

At Zoox, we are reimagining personal transportation from the ground up. As an Issue Resolution Engineer, you will play a critical role in ensuring the quality and build readiness of our autonomous vehicles during manufacturing. You will operate at the intersection of engineering and production, driving rapid containment and resolution of issues identified during general assembly and end-of-line validation. This role requires strong technical depth, urgency in execution, and the ability to lead cross-functional teams to root cause and implement durable corrective actions. You will partner closely with Vehicle Engineering, Manufacturing, Quality, Supplier Quality, and Operations to ensure vehicles meet Zoox’s quality standards and production targets. Your work will directly impact vehicle readiness, production efficiency, and overall fleet reliability. In this role, you will: Lead triage, containment, and resolution plan of issues identified during general assembly and end-of-line testing within your assigned subsystem/domain Define and execute short-term containment actions, including rework plans, part quarantine, and build flow protection Collaborate cross-functionally to lead root cause analysis across design, process, supplier, and manufacturing domains, identify and prioritize blockers, and drive Design for Manufacturing (DFM) improvements. Support cross-functional teams to implement permanent corrective actions (PCA) and prevent recurrence Support prototype builds, production trials, and engineering changes to validate fixes and improve manufacturability Develop and maintain metrics, dashboards, and reporting to track issue health, closure rates, and recurrence and improve PIRT processes, including issue tracking, prioritization, and cross-functional execution Qualifications B.S. or M.S. degree in Electrical Engineering or related technical field 8 to 12 years of experien

About the Team The Core Network Engineering team owns the end-to-end networking stack that connects OpenAI’s compute infrastructure — spanning global WAN/edge connectivity, data-center networking, and high-performance host/xPU networking used for large-scale training and inference workloads. This team is responsible for ensuring networking is never the bottleneck to model training efficiency, cluster reliability, or fleet expansion. They design and operate the systems that provide predictable, high-throughput, low-latency connectivity across some of the world’s most advanced AI infrastructure. About the Role We’re looking for engineers to help build and operate the networking foundation behind OpenAI’s frontier AI systems. Depending on your background and area of focus, you may work across host networking, datacenter fabrics, or global WAN infrastructure. The problems span low-level systems software, distributed infrastructure, protocol readiness, observability, performance engineering, automation, and large-scale network operations. You’ll work on systems where microseconds of latency, tail performance, and network reliability directly impact model training efficiency and production serving performance. This role is ideal for engineers who enjoy operating close to the hardware/software boundary and solving performance-critical infrastructure problems at massive scale. In this role, you will: Design, build, and operate networking systems that support large-scale AI training and inference infrastructure Improve performance, reliability, and scalability across host networking, datacenter fabrics, and WAN systems Develop automation for provisioning, configuration management, validation, upgrades, and lifecycle management of networking infrastructure Build tooling and observability systems for network health, performance analysis, debugging, and automated remediation Optimize network performance across technologies such as RDMA, RoCE, InfiniBand, Ethernet, and high-perf

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last-mile logistics in the long term. If you have a passion for applying robotics solutions in a service used by millions of people, then we want to talk to you! About the Role You will be a valuable and developing member of the Service Operations team at DoorDash Labs. You will build on your existing technical skills to perform diagnostic, maintenance, and repair work to keep our robot fleet and electric bicycles operating at peak performance, supporting our fleet utilization goals. You will work closely with Senior Service Technicians and your manager to expand your troubleshooting skills, gain deeper familiarity with our systems, and progressively take on more complex repairs. This is an on-site role with expectations of 100% in-office presence in Fremont, CA, San Jose, CA, or Sunnyvale, CA. You’re excited about this opportunity because you will… Perform standard and intermediate Service Technician tasks with growing independence, including service and upkeep of robotic systems and electric bicycles. Repair common faults in robotic platforms, modular components, electric bicycle drivetrains, and support vehicles using established troubleshooting procedures. Assist with complex or unusual faults alongside senior or lead technicians to learn advanced diagnostic methods for both robotic systems and e-bikes. Complete repairs on electrical systems, control units, battery packs, and hardware under guidance, with opportunities to develop toward independent advanced repairs. Use and interpret technical manuals, schematics, and diagnostic flowcharts to guide your work, applying these resources to both robot and electric bicycle service tasks. Document all diagnostic steps, repair actions, and component failures in the service management system to maintain accurate records and support fleet readiness. Learn from and collaborate with experienced technicians,

About the Team DoorDash Labs is a team within DoorDash building autonomous delivery robots and other autonomy solutions from the ground up for DoorDash's core delivery platform. If you have a passion for applying robotics solutions to a service loved by millions of people, then we want to talk to you! About the Role As an Operations Specialist in Autonomy Tech Support at DoorDash Labs, you will ensure the successful daily operations of the robot fleet and guide communication between Operations and Engineering teams to track and resolve field operations issues. You will report into the Operations Manager, Autonomy Tech Support and you will be 100% in-office and will require early and late shifts and shifts including weekends. You’re excited about this opportunity because you will… Be a primary contact for escalated software and hardware issues encountered during autonomy operations and testing Perform initial debugging and troubleshooting to capture important details to identify issue and implement resolution and mitigation steps Document new symptoms or failure modes that emerge in the field and work with engineering to determine appropriate mitigation steps Use trend analysis to report and triage anomalies, bugs and faults with necessary information to facilitate accurate Engineering investigation and resolution Create resolution steps documentation and maintain knowledge base We’re excited about you because… Comfortable with Linux command line, GitHub, Jira, and Service software Experience debugging and troubleshooting complex technical problems Prior experience with autonomous vehicles and/or robotics Willing to work flexible hours including weekends You are genuinely curious about how things work (or why they don’t) About DoorDash At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners

Instawork is on a mission to create meaningful economic opportunities for skilled hourly professionals in communities around the globe. Our AI-powered labor marketplace helps local businesses scale, and enables global technology companies to push the frontiers of robotics and AI. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we’re looking for exceptional talent to reimagine the way the world works. Instawork’s on-demand labor marketplace is uniquely valuable for robotics and physical AI. We’re working with leading frontier labs to create the highest-quality, highest-diversity datasets for training robotics foundation models. Instawork Robotics is the human advantage in the robotics revolution. We are seeking a highly skilled, Field Engineering Technician to manage the maintenance, calibration, and local deployment of a fleet of 600 custom wearable camera rigs. Unlike standard IT support, this role sits at the intersection of precision electronics, mechanical assembly, and field operations. You will be the primary guardian of our hardware integrity, ensuring that high-stakes egocentric data collection continues without interruption across various deployment sites. About IRL Researchers at UC Berkeley have identified a “100,000-year data gap” - the gulf between what trained AI language models and what physical robots actually have to learn from. Closing that gap is the defining infrastructure challenge of the physical AI era. IRL is Instawork’s answer to it. We deploy skilled workers into real commercial and residential environments - kitchens, warehouses, hotel floors, homes - to capture the high-fidelity task data that the world’s leading Robotics labs use to train their foundation models. Read more here . Who You Are: Field Engineering Technician – Wearable Devices Experience: 0–2 years Shift: Rotational Location: Bangalore Employment type: 1 year contract Role overview We are

The Team This role can sit in our NYC HQ on a hybrid basis, or it can be fully remote while working from a location based in either Eastern or Central time zones. We are looking for an experienced Senior Engineer for our SRE, Atlas team to support, maintain and grow the Atlas platform. As a senior SRE, you will be expected to be able to design & build complex systems, operate with autonomy and act as owner for everything you do. The SRE Atlas team works alongside the various Atlas software engineering teams to provide expertise about running systems at scale, build new tooling and automation and perform essential maintenance of the Atlas fleet. This is an SRE team, which means you can expect a highly hands-on approach, tackling the technical challenges of implementing large scale solutions that have the ability to impact our customer’s most crucial workloads. Role Overview We are seeking a talented Site Reliability Engineer (SRE) with a strong infrastructure background. This role requires engineers to have a customer-first mindset to ensure that everything we do results in a stronger product and a better experience for all Atlas customers. The ideal candidate should Have 5+ years of experience running critical systems at scale Value efficiency in processes and operations, and display a preference for automation over manual processes (“allergic to ops work”) Be familiar with a major cloud provider (AWS, Azure, or GCP) and possess the ability to build and operate systems in a multi-cloud environment A strong understanding of how to run a large scale Linux environment, including low level fundamentals Firm grasp of at least one modern programming language, beyond basic scripting (Go, Ruby, Python) Solid understanding of web and network protocols and standards (HTTP, TLS, DNS, etc) Special Requirements: Be a US Citizen Expectations Participate in the development of a reliable and resilient multi-cloud platform that hosts business critic

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Staff Software Engineer, you will orchestrate the implementation of vertical features and horizontal capabilities to include mentoring other engineers on defining requirements with stakeholders and communication tradeoffs of technical implementations on feature and capabilities until they are accepted by the stakeholders. You will: Orchestrate feature implementation across the Federal engineering team to ensure architectural consistency. Define technical strategy for agentic guardrails, explainability, and fleet orchestration. Ensure system reliability and performance across multiple security classifications and network types. Mentor engineers in the process of defining requirements with stakeholders and gathering acceptance. Communicate high-level technical trade-offs and implementation strategies to senior government stakeholders and Scale C-Suite members. Influence the long-term product strategy and technical roadmap for the Federal business unit. Consult on the architecture of AI-powered solutions for large-scale federal contracts. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in

As Senior Project Manager you will be responsible for overseeing the full project life-cycle of design and construction for Zoox’s various real estate assets. Our capital projects include a wide variety of typologies- from office and amenities to engineering/R&D, manufacturing, testing/proving grounds, fleet operations, fleet charging and fleet service sites. Project sizes, complexity and budgets will vary from $50K to $30M+. You will own project delivery beginning with pre-lease site due diligence and project planning all the way through project occupancy and close out. The c candidate will need to know all aspects of project delivery- including fiscal and schedule, design, construction and delivery. In this role, you will: Responsible for leading multiple capital construction projects of various complexity from initiation through close-out, owning the entire project lifecycle from pre-design through commissioning. Provide critical financial and schedule management, including creating and monitoring control systems for cost estimates, budgets, value engineering, schedules, and change orders, and reviewing/approving all architect, engineer, contractor, and vendor invoices. Partner with internal cross-functional teams to develop project programs, masterplan campus/city level projects, and collaborate with real estate teams on due diligence and lease negotiations. Manage procurement by sourcing appropriate team members (External PMs, Architects, MEP Engineers, and other trades) through the RFP process and contract execution, and by developing/recommending the project delivery method (Design-Build, Design-Bid-Build or other). Accountable for deliverables while tracking progress, driving all required entitlements, permits, and contracts, completing bid review and analysis for formal funding recommendations, and managing weekly and quarterly executive reports. Qualifications Bachelor’s or graduat

About the Team The Scaling team is responsible for the architectural and engineering backbone of OpenAI’s infrastructure. We design and deliver advanced systems that support the deployment and operation of cutting-edge AI models. Our work spans system software, networking, platform architecture, fleet-level monitoring, and performance optimization. About the Role We’re hiring an SW Engineer to enable production workloads and end-to-end testing on new platforms. This role will include creating new test harnesses and platform stress benchmarks, porting existing inference and training workloads to new, sometimes early-access, systems/hardware, analyzing performance and bottlenecks, and characterizing the end-to-end behavior of new systems (compute, comms, storage, control plane, and failure modes). Key Responsibilities Port and validate key inference and training workloads on new platforms/SKUs as they arrive; drive correctness, performance, and stability to an internal readiness bar. Build a suite of benchmarks and stress tests that capture real E2E behavior of our workloads by exercising all aspects of a system, including CPU, GPU, memory subsystem, frontend, scale-up, and scale-out networking (including WAN traffic, NVlink and RDMA collectives), storage, thermals, and any other relevant parts. Deep-dive performance on distributed training/inference: Collective performance and tuning (across NCCL/RCCL and internal libraries) Overlap of compute/communication, kernel-level bottlenecks, memory bandwidth and scheduling effects Create repeatable test harnesses that run in CI / lab environments and produce actionable outputs (pass/fail, performance score, regression detection). Partner with systems + fleet bring-up engineers to ensure the platform is not only stable and performant, but also operationally usable and scalable (containerization, K8s integration, telemetry hooks, failure triage loops). Work cross-functionally with vendors and internal stakeholders by producing

About the Team Our DD Labs team builds real-time autonomous delivery systems. The Planning & Decision-Making group is investing heavily in deep reinforcement learning to move beyond classical planning, learning policies that generalize across novel driving scenarios, handle long-tail edge cases, and improve continuously from large-scale fleet data. Our models jointly handle prediction and planning in a single unified architecture. Our stack is pure JAX end-to-end: the same code you train with is the code that runs on the robot. No C++ rewrites, no TensorRT export. A new policy goes from training to on-vehicle deployment in minutes. About the Role As a Senior/Staff Deep RL Engineer, you will design, train, and deploy deep reinforcement learning policies that make real-time driving decisions for our autonomous vehicles. You will own the full lifecycle, from problem formulation and reward design through large-scale distributed training to on-vehicle inference. You'll help define how learned components compose with the rest of the autonomy stack to produce robust, shippable behavior. You’re excited about this opportunity because you will… Formulate complex driving tasks as RL problems with well-shaped reward functions and expressive state/action representations. Design and train model-based deep RL agents using GPU-accelerated simulation at massive scale, including improving the simulator itself. Build and maintain distributed training infrastructure in JAX across large compute clusters. Build agentic optimization systems that automatically improve code, run experiments, analyze metrics, and iterate on RL policies with minimal human intervention. We’re excited about you because… BS/MS/PhD in CS, EE, Robotics, or a related field, with a strong foundation in reinforcement learning and deep learning. You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing,

The Program Management Office (PMO) at Zoox is responsible for driving cross-functional program planning and execution at the highest level. We partner with leaders from across the company in vehicle development, system design, software engineering, manufacturing, fleet operations, and business functions to develop and deliver major corporate milestones on the path to launch, and beyond. Our program managers contribute to the end-to-end success of technical, integrated product milestones involving both of our vehicle platforms - the Toyota Highlander test fleet and Zoox's purpose-built robotaxi. As a Technical Program Manager (TPM) for Core Autonomy Capabilities in PMO, you will own the portfolio of programs launching fundamental new autonomy and safety capabilities: fail-operational architectures, the next generation of the perception and motion planning stack, learned scene understanding and behavior models, collision avoidance, and the guidance and routing capabilities that expand where the vehicle can drive. These are new capabilities rather than refinements of shipped ones, and they sit on the critical path to launch. This is a high-leverage, high-visibility portfolio role. Rather than a single subsystem, you will own several capability programs running concurrently, partnering with the TPMs who drive them and driving programs directly where no dedicated owner exists. The engineering, validation, and safety teams behind this work sit across several organizations outside your reporting line, so building credibility quickly and driving decisions without formal authority is core to the job. In this role, you will: Own the outcome for each capability. Drive programs from architecture through the release that ships them, and define what "done" means when completion criteria are still being established. Partner with the TPMs who own individual capabilities. Set a consistent bar for how their programs are planned and reported, and unblock what the

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. As a Staff Software Engineer on our Inference team , you will work end to end, identifying and addressing key infrastructure blockers to serve Claude to millions of users while enabling breakthrough AI research. Strong candidates should have familiarity with performance optimization, distributed systems, large-scale service orchestration, and intelligent request routing. Familiarity with LLM inference optimization, batching strategies, and multi-accelerator deployments is highly encouraged but not strictly necessary. Strong candidates may also have experience with: High-performance, large-scale distributed systems Implementing and deploying machine learning systems at scale Load balancing, request routing, or traffic management systems LLM inference optimization, batching, and caching strategies Kubernetes and cloud infrastructure (AWS, GCP) Pytho

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a Technical Program Manager on the Compute team, you will help drive the planning, coordination, and execution of programs that keep Anthropic's compute infrastructure running efficiently at scale. Our compute fleet is the foundation on which every model training run, evaluation, and inference workload depends. You'll join a small, high-impact TPM team and take ownership of critical workstreams across the compute lifecycle, from how supply is procured and brought online, to how capacity is allocated and utilized across teams. The exact focus will depend on your strengths and the team's evolving needs. You'll partner with Infrastructure, Systems, Research, Finance, and Capacity Engineering to shape the processes, tooling, and coordination mechanisms that allow Anthropic to move fast while managing an increasingly complex compute environment. Responsibilities: Own and drive critical programs across the compute lifecycle, coordinating execution across multiple engineering, research, and operations teams Build and maintain operational visibility into the compute fleet, ensuring the organization has a clear picture of supply, demand, utilization, and health Lead cross-functional coordination for compute transitions: bringing new capacity online, migrating workloads, and managing decommissions across cloud providers and hardware platforms Partner with engineering and research leadership to navigate competing priorities and drive alignment on how compute resources are planned, allocated, and used Identify and close operational gaps across the compute pipeline, whether through new tooling, improved processes, or better cross

Join the engineering teams that bring OpenAI’s ideas safely to the world!! The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role We’re building the observability product for OpenAI—from scalable infrastructure to a rich, AI-powered UI. Our systems ingest over petabytes of logs and billions of time series metrics across our fleet. We're now layering intelligence on top—think agents that summarize SEVs, auto-generate dashboards, or help engineers debug through notebook-like UIs. We’re hiring software engineers across the stack—infra, backend, and product. You’ll join a small, gritty team building both foundational infra and novel internal tools to make OpenAI's production systems reliable, performant, and observable. What You’ll Do Own core observability infrastructure, including distributed logging, time series, and trace storage Build AI-native tools that help engineers detect, understand, and resolve issues autonomously. Contribute to UI experiences like dashboards, notebooking, or interactive debugging Collaborate closely with engineers, researchers, user ops, and other teams across the company to build the next generation observability product You Might Be a Fit If You: Have operated large-scale distributed systems in production. ( especially logging systems or some other time series databases) Thrive in ambiguous environments and roll up your sleeves to solve unscoped problems. Have full-stack chops or product sensibilities—you're excited to build real tools people use. Have strong fundamentals in systems, networking, and cloud infra (Kubernetes, AWS, etc). Bonus : built or contributed to observability systems (e.g. Prometheus, OpenTelemetry, etc). Why This Team We’re b

This is Adyen Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. Android - AOSP Engineer - Device Foundations Adyen’s device foundations and fleet of payment devices is growing exponentially with every passing month. We are bringing thousands of devices to the field every month with a wide variety of models and this doesn’t come without challenges. We are looking for an Android Engineer with AOSP experience to help us in taking full control over the Android OS. What you will do: Lead the Android AOSP efforts in order to build a strong and flexible foundation for our Android payments application Engage in cross-functional conversations with product management, software engineering and hardware engineering teams to ensure the best payment experience for our merchants Drive conversations with SOC (system on chip) vendors and terminal vendors in order to secure high performing components Ensure software quality by using the latest technologies and frameworks in Android OS engineering Coach team members to grow the team with the right skill set Who you are: 5+ years of experience working with the Android OS. In-depth understanding of the Android OS, spanning from secure boot and the Linux Kernel up to the Java Framework integration. Proficient in C/C++. Knowledge of Java and/or Kotlin is a plus. Experience working with source control tools such as Git, Repo, Gerrit, GitHub, and with Androi