Fleet Operations Associate Manager Jobs

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. Data and analytics are at the heart of Lyft’s products and decision-making. As a member of the Lyft Urban Solutions team, you will play a key role in shaping the future of bikeshare by leveraging data to operational needs and city partners. In this role, you will collaborate closely with Operations, Science, and Finance teams to drive data-driven strategies that align our operations with city transportation goals. You will work in a fast-paced environment where analytical insights directly impact fleet management, operator performance, pricing, rider accessibility, and long-term investments in bikesharing infrastructure. We’re looking for a passionate and driven Data Analyst Intern to tackle some of the most complex and impactful challenges in bikesharing. If you’re excited about shaping the future of urban mobility through data, we’d love to hear from you. Responsibilities: Partner with Operations, Engineering, Data Science & Analytics, Product, Finance and other cross-functional stakeholders to manage and update key business logic Develop frameworks and scalable processes to streamline reporting, drive decision-making and prioritization Define the metrics used to measure the success of strategic initiatives and system health; build dashboards to monitor metrics performance over time Work closely with cross-functional partners to deliver data quickly, reliably and accurately to our city partners Monitor and diagnose KPI performance and present findings to senior leadership Experience: Currently pursuing a Bachelors or Masters degree in mathematical sciences (Operations Research, Computer Science, Statistics, Applied Mathematics, Theoretical Physics, Behavioral Science, Electrical Engineering, etc.), Economics (Microeconomics Theory, Econometrics etc.), Data Engineering; or a related field;

*We're Hiring Growth & Market Research Intern* *Company:* RAMP GLOBAL *Location:* Hyderabad (Work from Office) *Duration:* Minimum 3 Months *Stipend:* 6,000 10,000/month *PPO Opportunity* for high-performing interns *Build Your Career Beyond the Classroom!* Are you a recent graduate or final-year student looking to gain real business experience? At *RAMP GLOBAL*, you'll work closely with the Founder's Office, interact with real customers, conduct market research, and learn how products are built, tested, and launched. This is a hands-on internship where you'll contribute to real business projects not just routine tasks. ### What You'll Work On Customer interactions & business communication Market & competitor research Customer interviews & feedback analysis Business outreach & partnership support Presentations, reports & business insights Product & go-to-market initiatives ### What You'll Learn • Business Development Fundamentals • Market Research & Customer Discovery • Professional Communication • Analytical & Presentation Skills • Startup Execution & Problem Solving • Working with Founders & Leadership ### Who Can Apply? Recent graduates or final-year students (Any Technical or Non-Technical background) Fluent in English, Hindi & Telugu Good communication skills Curious, proactive, and eager to learn ### Why Join Us? Learn directly from experienced founders Work on real-world business challenges Build practical, career-ready skills Internship Certificate PPO opportunity based on performance *About RAMP GLOBAL* RAMP GLOBAL develops innovative software solutions for fleet management, vehicle maintenance, and workshop operations, serving businesses across multiple countries. Learn more: rampglobal *How to Apply?* Send us your updated resume at . Shortlisted candidates will complete a short practical assignment before the interview process.

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. As a Frontend Software Engineer on the Operator Core Tooling pod, you'll play a vital role in building the robust services that power our critical operations tooling platform. Your work will directly empower our micromobility operations teams by providing them with intuitive and efficient tools, significantly improving their daily workflows as they manage our fleet. You'll collaborate closely with business leaders, front-end developers, and data scientists across Lyft to achieve this impact. Responsibilities: Help define the roadmap and architecture based on technology and business needs Write well-crafted, well-tested, readable, maintainable code Have a good grasp and ability to explain the various tradeoffs made in decisions Participate in code reviews to ensure code quality and distribute knowledge Lead projects from idea to positive execution Incorporate considerations for business context and failure modes in your work Proactively participate in resolving ongoing incidents Unblock, support, effectively communicate and obtain buy-in across teams to achieve results Share your knowledge by giving brown bags, tech talks, and evangelizing appropriate tech and engineering best practices See the direct impact of your work on the efficiency of our operating teams Experience: 3+ years of software engineering industry Advanced knowledge of JavaScript Experience working with modern JavaScript frameworks, like React Experience working with NodeJS and Express applications Experience working with design systems (e.g. Bootstrap, Salesforce Lightning, GitHub Primer) Good understanding of web performance and how browsers and DOM work Experience with unit, integration, and end-to-end testing Experience designing, building and improving a set of team owned components Culture of investigating and solvin

About the job Build the cloud platform that turns Graphcore AI systems into usable, scalable services. Graphcore needs a Bristol-based Staff Cloud Engineer to develop and deploy private and public cloud services for AI compute. You will join the Cloud Platform team within Software Platform, close to datacentre operations and product development. Your work will shape how internal users and customers access large-scale AI systems. You will keep critical infrastructure available while helping pre-release hardware and software become reliable cloud services. You will operate and extend OpenStack-based services, automate deployment with infrastructure-as-code, and improve observability across the fleet. You will benchmark, validate and optimise systems spanning Graphcore hardware, servers, switches and storage. This role suits someone who wants ownership of hard infrastructure problems, not a narrow ticket queue. Expect unproven components, direct user feedback, and decisions that move quickly into production. The team and culture The Cloud Platform team turns Graphcore products into large-scale AI solutions for internal users and customers. Work happens close to the systems, with engineers deploying, measuring and improving services directly. You will work with Software Platform, Datacentre Operations, Product Development, Engineering and QA. The team values people who take responsibility for unclear problems and make progress without waiting for perfect inputs. The team makes decisions from evidence: metrics, benchmarks, user impact and system behaviour. Engineers speak up, surface risks early and own corrective actions when systems need attention. What we’re looking for A relevant degree or equivalent practical experience, with proven ability to scope and deliver technical infrastructure work. Experience operating on-premises or private-cloud environments, with strong ownership of end-user availability. Strong Linux system administration and scripting sk

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role OpenAI's Hardware organization builds supercompute platforms from silicon and boards to full rack-scale systems to power advanced AI workloads. This role owns end-to-end quality for high-speed interconnect hardware across the product lifecycle: early design influence, supplier/contract manufacturer readiness, qualification, ramp, and fleet quality in lab and data center environments. You will be the quality lead for advanced interconnect components and assemblies, including high-speed copper cables, cable cartridges, patch panels, backplane/cable-backplane solutions, high-speed connectors, and related electro-mechanical interfaces. You will partner closely with electrical, mechanical, SI/PI, systems, reliability, operations, and external vendors to prevent escapes and drive rapid, data-driven containment and corrective action. In this role you will: Own quality for advanced interconnect components and assemblies: high-speed connectors, high-speed copper cables, cable cartridges (e.g., cable cassette style assemblies), patch panels & optics, and backplane/cable-backplane interconnect solutions. Drive quality-by-design: participate in design reviews, DFM/DFx, tolerance stacks, material and plating selections, connector mating strategy, strain relief, and assembly methods to reduce variation and field failures. Define and track quality and reliability metrics (DPPM, yield, escapes, RMA/FRACAS trends, Cpk/Ppk where applicable) for interconnects across NPI and m

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. The Regional People Partner, Employee Relations Lead serves as the centralized employee relations partner for our Airport Operations team, with direct, hands-on support for one region. In this role, you're the consistent thread ensuring employee relations issues are handled the same way, every time, no matter where they happen. You're the person leaders lean on to make good calls, and the person team members know is invested in their success. This role puts you in the middle of it all — maintaining oversight across the entire fleet while coaching station leaders, resolving employee relations issues with consistency and fairness across the field, and building an exceptional team member experience that helps CLEAR thrive. What you'll do: Be the go-to People Partner for Operations leaders in your region - the person they call when something's tricky, not just when something's already broken Coach and sharpen station leaders and managers - through training, real feedback, recognition that means something, and just showing up when it counts Own employee and labor relations across your stations: run investigations, dig into root causes, and land on outcomes that are fair and consistent, working closely with Legal along the way Turn employee data, survey results, and what you're hearing on the ground into recommendations leaders can actually act on Partner across People and Operations on the bigger initiatives: onboarding, process fixes, and making sure People practices run the same way at every station Lead timely, thorough, and object

Location : Come and join us in Barcelona! Freenow by Lyft empowers smarter mobility decisions helping people to move freely and cities to thrive. One of our core goals for 2026 is the complete digitalization of the European taxi market. We work with taxi companies to provide them with our advanced dispatch and fleet management software completely free of charge. This enables them to significantly reduce operating costs, successfully differentiate themselves from major ride-hailing providers, and manage a profitable, sustainable business. To support this, we are looking for a Sales Manager who will become the face of this initiative. We look forward to your application and can't wait to have you on board for this journey! As we are an international company, we ask that you submit your application documents in English. YOUR DAILY ADVENTURES WILL INCLUDE: Prospect, engage, travel and pitch our Dispatch tool to SME taxi companies in Spain. You are the driving force behind converting traditional vehicle fleets into modern, connected Freenow by Lyft partners. Guide entrepreneurs, fleet owners, and senior dispatchers through the fear of operational change. Act as the voice of our partners. You will gather on-the-ground feedback about our software and collaborate directly with our Product and Strategy teams to help "co-build" the ultimate solution. TO BE SUCCESSFUL IN THIS ROLE: 3-5 years of professional experience in areas such as B2B business development, sales, or account management. Experience in mobility, logistics, or selling SaaS solutions to SMEs is especially valued. Proven track record of managing a B2B pipeline and handling objections. You understand that even when a product is free, you still have to expertly "sell" the time, effort, and operational shift required to adopt it. Strong communication skills with the ability to build trust and long-term relationships. The ability to deeply understand a partner's business operations at a process level. You are s

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

NVIDIA is seeking a Senior Staff SRE to build and operate reliable, scalable compute platforms that support global engineering workloads. This role spans Kubernetes, KubeVirt, bare-metal infrastructure, automation, observability, and AI-enabled operations. Join a team that solves complex infrastructure challenges, builds durable automation, and improves the reliability and operational experience of critical compute services. What you’ll be doing: Build, operate, and improve large-scale Kubernetes, KubeVirt, Linux, container, and bare-metal compute platforms, with a focus on performance, capacity, reliability, and operational scale. Lead bare-metal provisioning and lifecycle management in data centers, including PXE boot, DHCP, DNS, OS provisioning, hardware validation, and fleet automation. Develop automation, self-service capabilities, and observability solutions using APIs, Python or Go, Infrastructure as Code, configuration management, metrics, logs, traces, and service-health data. Define and operate SLOs, SLIs, error budgets, alerting, and incident-response practices; lead complex incident investigations, corrective actions, and blameless postmortems. Partner with infrastructure, security, hardware, data-center, and application teams to deliver global platform initiatives, and participate in an on-call rotation. What we need to see: BS in Computer Science, Engineering, a related technical field, or equivalent experience, plus 10&#43; years operating production infrastructure or platform services. Strong expertise in Kubernetes administration, KubeVirt, Docker, containerization, microservices, Linux systems, and resolving distributed-system challenges. <l

About the Team The OpenAI Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role OpenAI Robotics depends on high-quality real-world robot data from a large, live operational environment. That environment has many deployed workcells, changing configurations, and little tolerance for downtime. We are seeking a Field Engineer to help keep that environment running well. You will own the day-to-day technical health of robotic workcells used in ongoing data acquisition operations, diagnose and resolve failures across hardware and software, and build the practical tools, documentation, and support workflows that make operators and technicians more effective. The work is close to the floor, close to the failure modes, and close to the research impact. This role sits at the intersection of software, robotics hardware, and live operations. The best people in it are practical, technically sharp, calm under pressure, and motivated by making real systems work reliably at scale. This role will be based in San Francisco, CA 5 days per week and offer relocation assistance to new employees. In this role, you will: Serve as an engineering owner for keeping a fleet of robotic workcells online in daily operation. Diagnose, fix, mitigate, or escalate issues spanning mechanics, electronics, controls, software interfaces, logs, and configuration. Partner closely with technicians, operators, and engineering teams to improve scalable fleet support processes. Build or spec lightweight hardware and software tools that improve monitoring, diagnostics, recovery, and handoffs. Create documentation, SOPs, and diagnostic playbooks that turn en

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

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