Fleet Operations Associate Manager Jobs

Senior Product Manager, Robotics & Autonomy What we're doing isn't easy, but nothing worth doing ever is. At Diligent Robotics, we envision a future powered by robots that work seamlessly with human teams. We build artificial intelligence that enables service robots to collaborate with people and adapt to dynamic human environments. Our robots operate every day in hospitals, helping healthcare staff spend less time on routine work and more time caring for patients. Operating a real-world fleet gives us something few robotics companies have: continuous customer feedback and operational data that directly shapes the next generation of Physical AI. We're looking for a Senior Product Manager, Robotics & Autonomy to define and execute the product strategy for some of the most critical capabilities in our robotics platform. You'll work at the intersection of robotics, autonomy, AI, and software engineering to translate business priorities, customer needs, and technical opportunities into a clear product roadmap that drives measurable outcomes. This role is ideal for someone who understands complex autonomous systems and enjoys working alongside world-class engineers to bring ambitious technology from concept into production. Responsibilities Own the product strategy and roadmap for key Robotics and Autonomy initiatives, balancing customer impact, technical feasibility, and long-term platform investments. Define product requirements for autonomy, navigation, perception, fleet intelligence, simulation, and robotics platform capabilities. Partner closely with Engineering, AI, Robotics, Customer Success, Operations, and Leadership to align priorities across the organization. Translate customer feedback, fleet telemetry, and operational insights into product decisions that improve robot performance, reliability, and user experience. Prioritize investments using data, customer value, technical complexity, and business impact. Drive cross-functional execution from concep

About the Role At Together AI, you’ll build and operate one of the world’s largest GPU fleets used for frontier model training and inference. This isn’t a traditional infrastructure role—we’re looking for engineers who love building systems, automating everything, and solving problems at massive scale. If you enjoy writing software more than clicking dashboards, obsess over eliminating manual work, and want to build infrastructure that manages tens of thousands of GPUs autonomously, we’d love to talk. Responsibilities Design and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention. Build AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation. Develop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers. Build software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators. Create automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads. Build internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations. Continuously improve deployment velocity, reliability, and operational efficiency through automation. Partner closely with hardware, networking, platform, and AI teams to push the limits of AI infrastructure. Requirements 3+ years building distributed systems, infrastructure platforms, or large-scale backend software. Strong software engineering skills in Python, Go, or Rust . Experience building platforms, automation systems, or developer infrastructure. Experience with Linux, Kubernetes, Terraform, Ansible, or similar infrastructure technologies. Strong systems thinking with the ability to understand problems across hardw

About the Role In this role, you will operate, scale, and optimize multi-petabyte storage systems purpose-built for the world’s largest AI training and inference workloads. You’ll manage and scale high-performance parallel filesystems and object stores, evaluate and integrate cutting-edge technologies such as Vast, Weka, Ceph, and Lustre, and solve the complex engineering challenges of operating at extreme throughput, low-latency data paths, and massive cluster-scale storage operations. You will also build Kubernetes-native storage operators and self-service platforms that provide automated provisioning, strict multi-tenancy, performance isolation, and quota enforcement at cluster scale. Day-to-day, you’ll optimize end-to-end data paths for 10-50 GB/s per node, design multi-tier caching architectures, implement intelligent prefetching and model-weight distribution, and tune parallel filesystems for AI workloads. Responsibilities Architect and implement the technical strategy and storage roadmap for Together AI, driving high-performance architectural decisions as we scale our GPU fleet. Engineer and scale multi-petabyte AI/ML storage systems by integrating Vast, Weka, and Ceph while executing deep cost optimization through automated tiering and lifecycle policies. Develop intelligent caching and tiered storage architectures to achieve extreme IOPS and cluster-wide throughput at GPU scale for training and inference workloads. Tune storage isolation at the L2/L3 network layers to ensure secure, production-grade multi-tenancy for storage clients. Code Kubernetes storage operators and controllers to enable automated provisioning, self-service abstractions, and quota enforcement. Engineer end-to-end data paths to achieve 10+ GB/s per GPU node; architect multi-tier caching for model weights and datasets; tune parallel filesystems using advanced profiling; and scale storage infrastructure across thousands of nodes. Optimize end-to-end data paths through advanced

About the Role At Together AI, you’ll build and operate one of the world’s largest GPU fleets used for frontier model training and inference. This isn’t a traditional infrastructure role—we’re looking for engineers who love building systems, automating everything, and solving problems at massive scale. If you enjoy writing software more than clicking dashboards, obsess over eliminating manual work, and want to build infrastructure that manages tens of thousands of GPUs autonomously, we’d love to talk. Responsibilities Design and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention. Build AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation. Develop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers. Build software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators. Create automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads. Build internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations. Continuously improve deployment velocity, reliability, and operational efficiency through automation. Partner closely with hardware, networking, platform, and AI teams to push the limits of AI infrastructure. Requirements 3+ years building distributed systems, infrastructure platforms, or large-scale backend software. Strong software engineering skills in Python, Go, or Rust . Experience building platforms, automation systems, or developer infrastructure. Experience with Linux, Kubernetes, Terraform, Ansible, or similar infrastructure technologies. Strong systems thinking with the ability to understand problems across hardw

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

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

About the Team: GTM Innovation is a product engineering team with a charter to automate 100% of digital knowledge work in OpenAI's GTM, so sellers spend more time directly with customers. AGI-level reasoning doesn’t mean organization-level transformation “just works” out of the box; orgs must be redesigned around abundant intelligence and persistent virtual coworkers. Our team builds and scales a fleet of virtual coworkers that operate as full-time members of the account team, and redefines how our human-first revenue organization interacts with their agentic teammates. About the Role We’re looking for Full Stack software engineers with a product mindset to join the GTM Innovation team. As a product engineer on this team, you’ll help OpenAI meet the world at scale. You’ll partner closely with go-to-market teams to understand their workflows, identify leverage points, and ship novel solutions using OpenAI’s API platform. You’ll move quickly from prototype to production, and your work will directly shape how customers experience our technology in the field. This role is ideal for engineers who want to be close to users, own end-to-end outcomes, and help define entirely new categories of enterprise software. In this role, you will: Build high-impact applications and tools that accelerate OpenAI’s go-to-market efforts Work across the full product lifecycle for GTM: prototype, iterate, ship, and maintain Embed with Sales, Technical Success, and Revenue Operations to identify user needs and build for them Apply OpenAI’s models in novel ways to solve real-world customer and internal workflow problems Translate learnings into feedback for Applied and Research teams to inform product development You’ll thrive in this role if you: Have 4+ years of experience as a software/ML/product engineer working on user-facing systems Former founder, or early engineer at a startup who built a product from scratch is a plus Are fluent in Python or JavaScript and comfortable building full-s

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. At Okta, our motto is "Always On" and nowhere do we embrace that more than in Technical Operations. We strive to build the most reliable and performant systems on the planet through the skillful use of automation. If you like to be challenged and have a passion for solving large-scale automation, testing, and tuning problems, we would love to hear from you. The ideal candidate is someone who exemplifies the ethics of, “If you have to do something more than once, automate it” and who can rapidly self-educate on new concepts and tools. You will work on: Leading the architecture, design and rollout of the internal developer platform which would span CI/CD, tooling, infrastructure as code (IAC) integrations as well as modernization efforts Enhance existing automation for fleet management and build new features as per the needs of the infrastructure platform Spearhead initiatives and projects that enhance engineer productivity by identifying and mitigating bottlenecks in the development flow Mentoring, managing, and leading a team of SWEs & SREs with a broad range of expertise and experience Triaging and troubleshooting complex production issues to ensure reliability and performance. Working closely with our stakeholders across the organization to ensure our new capabilities are aligned to our competing constraints of reliability, security, and delivery velocity Partnering directly with recruiting and people ops to hire and retain the best talent

About the Role At Together AI, you’ll build and operate one of the world’s largest GPU fleets used for frontier model training and inference. This isn’t a traditional infrastructure role—we’re looking for engineers who love building systems, automating everything, and solving problems at massive scale. If you enjoy writing software more than clicking dashboards, obsess over eliminating manual work, and want to build infrastructure that manages tens of thousands of GPUs autonomously, we’d love to talk. Hybrid at our office in Amsterdam or Remote in the UK. Responsibilites Design and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention. Build AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation. Develop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers. Build software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators. Create automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads. Build internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations. Continuously improve deployment velocity, reliability, and operational efficiency through automation. Partner closely with hardware, networking, platform, and AI teams to push the limits of AI infrastructure. Requirements 3+ years building distributed systems, infrastructure platforms, or large-scale backend software. Strong software engineering skills in Python, Go, or Rust . Experience building platforms, automation systems, or developer infrastructure. Experience with Linux, Kubernetes, Terraform, Ansible, or similar infrastructure technologies. Strong systems thinkin

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft connects people to transportation to change the way we live and get around our communities. Lyft Urban Solutions (LUS) is North America’s leader in micromobility. We own, operate, or provide hardware and software solutions for bikeshare and scootershare programs in 57+ global markets including Montreal, London, New York City, Mexico City and others. Our rapidly growing active fleet includes state-of-the-art charging stations, electric bikes, and scooters, and services hundreds of millions of rides per year. The Hardware Product and Industrial Design Team at LUS is responsible for conceiving, guiding development of, launching, and sustaining world-class products used by riders, cities, and operators over the world. We represent LUS in micromobility forums, engage directly with customers, and guide research and development. We aim to ensure all products we develop are delightful for riders, globally competitive, elegant, and future-facing. We are looking for an exceptional Senior Product Manager, Hardware to manage our existing stations portfolio as well as develop our next generation of stations products. Our stations are now as iconic in cityscapes as London Routemaster buses of old. You will have end-to-end ownership of new station product development, leading a cross-functional team through all phases of hardware development to launch, and will be responsible for a fleet of over 300,000 charging and non-charging station assets already on the ground. You will engage directly with LUS leadership, engineering, data science, operations, and design to achieve the company’s vision for reinventing transportation. You will work closely with our Vehicles Product Manager, Industrial Design team, and counterparts in software product management to ensure ou

This is where your work makes a difference. At Baxter, we believe every person—regardless of who they are or where they are from—deserves a chance to live a healthy life. It was our founding belief in 1931 and continues to be our guiding principle. We are redefining healthcare delivery to make a greater impact today, tomorrow, and beyond. Our Baxter colleagues are united by our Mission to Save and Sustain Lives. Together, our community is driven by a culture of courage, trust, and collaboration. Every individual is empowered to take ownership and make a meaningful impact. We strive for efficient and effective operations, and we hold each other accountable for delivering exceptional results. Here, you will find more than just a job—you will find purpose and pride. Your Role at Baxter The Field Service Technician I will perform functions related to product readiness for patient utilization on a wide range of rental and customer owned medical products . This is where we transform healthcare together by cleaning, disinfecting, operational function checks, and minor repairs of Baxter and non-Baxter products. Explore a Day in the Life of a Field Service Technician and learn more about Field Service Careers here . Every repair, every delivery, and every call makes a real impact. In addition to the repair work, the FST I is also responsible for performing the same responsibilities as a FST I related to product readiness for patient utilization on a wide range of rental and customer owned medical products. This position requires operating a fleet vehicle in a safe manner as well as direct customer contact. Additionally, will provide 24/7 delivery, removal, and service support for products in service centers and customer accounts in a timely and professional

About the team DoorDash Labs is an independent robotics group within DoorDash working on autonomous solutions for the core business. This is the team that builds Dot, our self driving delivery robot designed from the ground up. If you are passionate about deploying autonomous technology at scale, then we want to talk to you. About the Role As a software engineer on the data visualization team you will own the applications used to introspect robot data. Bridge the gap between sensors, logs, diagnostics, telemetry, mission intel, and a diverse set of users across the Dot team. You will be expected to architect and develop systems with a high degree of autonomy. You will set roadmaps, identify opportunities for new systems, and execute. The applications you build should be intuitive, practical, and delightful to use. This role requires end to end ownership of both backend and frontend systems. You're excited about this opportunity because you will… Build tools that help users across autonomy, operations, product, and executive teams understand robot behavior both on-road and in simulation Expand upon extensive web tooling for interaction with time series data, video playback, and 3D scene reconstruction Maintain a robust C++ visualization framework for transforming robot data into informative and beautiful 2D and 3D web output Develop a portfolio of data introspection capabilities to support an expanding fleet of next generation robots Maintain a high bar for quality and take pride in your work! We’re excited about you because you… Are passionate about web technologies, game development, 3d computer graphics Have an eye for UX and empathy with a wide range of users Have experience in Robotics, self driving, scientific visualization, simulation High performance browser technologies (WebCodecs, Web Workers) 3D technologies (WebGL, three.js , Open3D) or game engines Distributed/batch compute (Ray, Temporal, Buildkite, Docker, Kubernetes) AWS infra (ECR, S3, lambda, api-ga

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are looking for a Senior Staff Site Reliability Engineer to join our team. This is a hybrid role based in Bangalore, reporting to the Director, Engineering in the Production Engineering and Reliability team in India. You will own the reliability and operational integrity of a global fleet spanning GCP, AWS, and bare-metal infrastructure — building self-healing automation, hardening provisioning workflows, and embedding observability into every layer of the platform. What you’ll do (Role Expectations) Develop production-grade automation in Ansible, Go for bare-metal provisioning, IPMI/Redfish-based hardware lifecycle operations, and autonomous remediation Design and implement fault-tolerant provisioning systems with self-healing and auto-remediation capabilities Develop telemetry pipelines for hardware and system monitoring — integrating metrics, logs, and distributed tracing (Pro

About the Team Compute Foundations builds the software that manages OpenAI’s GPU compute infrastructure across sites, data centers, and infrastructure providers, supporting model training and inference. Our systems turn large, heterogeneous fleets of machines into dependable compute for research and products. We build Kubernetes-based control planes, controllers, services, and APIs that coordinate the lifecycle of machines and clusters. We connect global infrastructure management with the realities of bare-metal systems, giving clients consistent interfaces across differences in hardware, topology, and provider behavior. About the Role You will build distributed systems that provision, configure, and manage compute throughout its lifecycle. Your work will connect global services and Kubernetes controllers with the systems that bring machines online, update them safely, and recover them when something goes wrong. This role combines software architecture with an understanding of how machines and data centers work. You might design a lifecycle API, improve controller performance under high concurrency and provider rate limits, or trace a provisioning failure from an API through reconciliation to network boot or host configuration. You will help these systems remain reliable as the fleet expands across sites and generations of GPU hardware. We value depth in relevant systems and the ability to connect layers. You do not need to arrive as an expert in every component of the stack. In this role, you will: Design, build, and operate Kubernetes-based controllers and distributed services that coordinate infrastructure across sites, isolate failures, and scale as GPU capacity grows. Define APIs and resource models that let clients request and track lifecycle operations through consistent interfaces across hardware platforms and providers. Build provisioning and configuration services that coordinate network boot, hardware management interfaces, and the deployment of firmware,