Fleet Operations Specialist Jobs

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 As a software engineer on the Scaling team, you’ll help build and optimize the low-level stack that orchestrates computation and data movement across OpenAI’s supercomputing clusters. Your work will involve designing high-performance runtimes, building custom kernels, contributing to compiler infrastructure, and developing scalable simulation systems to validate and optimize distributed training workloads. You will work at the intersection of systems programming, ML infrastructure, and high-performance computing, helping to create both ergonomic developer APIs and highly efficient runtime systems. This means balancing ease of use and introspection with the need for stability and performance on our evolving hardware fleet. This role is based in San Francisco, CA, with a hybrid work model (3 days/week in-office). Relocation assistance is available. In this role, you will: Design and build APIs and runtime components to orchestrate computation and data movement across heterogeneous ML workloads. Contribute to compiler infrastructure, including the development of optimizations and compiler passes to support evolving hardware. Engineer and optimize compute and data kernels, ensuring correctness, high performance, and portability across simulation and production environments. Profile and optimize system bottlenecks, especially around I/O, memory hierarchy, and interconnects, at both local and distributed scales. Develop simulation infrastructure to validate runtime b

As a Perception Engineer, you will be instrumental in designing and implementing cutting-edge detection models, utilizing fused sensor data. In particular, the role will be on advanced projects that are aimed at the next generation of driving software, including looking at joint detection and tracking models as well as ways to send rich embeddings to downstream models to relay semantic meaning and capture uncertainty. This role offers a unique opportunity to directly impact Zoox's expansion into new areas. By developing more generalizable and adaptable models, you will help us navigate diverse and challenging circumstances, accelerating our mission to deliver safe and reliable autonomous mobility. We are looking for a highly motivated individual passionate about pushing the boundaries of perception in the autonomous vehicle space. In this role, you will: Train ML models, perform various studies into incorporating SOTA approaches as well as ablations/modifications of existing models Document experimental outcomes and drive towards deploying these models into Zoox robots Visualize your data at the input and output to understand the issues Collaborate with teams such as ML optimization, data labeling, metrics and planner to ensure project is successful for Zoox releases Qualifications MS/PhD in Computer Science or related field Experience with PyTorch or related ML frameworks Experience deploying learned models into production Excellent collaboration and teamwork skills with proven track record of working on large-scale problems Bonus Qualifications Prior experience in the AV or related space with joint detection and tracking models Deep understanding of how to setup end-to-end training and evaluation processes About Zoox Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting a

RDQ226R605 This role can be based remotely anywhere in the United States. About Databricks Databricks is the data and AI company. More than 12,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. About the Team The Agentic Security Engineering team is a horizontal, shared services engineering team that makes every Databricks security function AI-native — building the AI agents, "personas," and shared platform that security teams across the org (Detection & Response, Threat Intelligence, Vulnerability & Product Security, Red Team, GRC, and Continuous Monitoring) build on to operate at machine speed, safely and reliably. We leverage AI to transform how security is done. The Role As Staff Security Software Engineer , you own a major technical workstream designing and shipping production-grade AI agents and the platform capabilities that power them, with reliability, observability, and safe-by-default security as first-class requirements. You set the standards for how agents are built and operated and co-build with partner security teams. Example use cases you'll enable, led by AI threat detection at scale (alert triage and false-positive reduction, fleet-scale anomaly detection), extend to threat hunting, vulnerability management, product security, red team/offensive testing, and GRC/assurance use cases. The Impact You Will Have Agentic Security Engineering Architecture Design, ship, and operate production AI agents/personas that security teams depend on, starting with AI threat detection at scale. Build and harden the shared platform so any security team can ship agents safely and reliably — i.e., sandboxing, scoped least-privilege identity, obs

About the Team Our Inference team brings OpenAI’s most capable research and technology to the world through our products. We empower consumers, enterprise and developers alike to use and access our start-of-the-art AI models, allowing them to do things that they’ve never been able to before. We focus on performant and efficient model inference, as well as accelerating research progression via model inference. About the Role We are looking for an engineer who wants to take the world's largest and most capable AI models and optimize them for use in a high-volume, low-latency, and high-availability production and research environment. In this role, you will: Work alongside machine learning researchers, engineers, and product managers to bring our latest technologies into production. Work alongside researchers to enable advanced research through awesome engineering. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our model inference stack. Build tools to give us visibility into our bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues. Optimize our code and fleet of Azure VMs to utilize every FLOP and every GB of GPU RAM of our hardware. You might thrive in this role if you: Have an understanding of modern ML architectures and an intuition for how to optimize their performance, particularly for inference. Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done. Have at least 5 years of professional software engineering experience. Have or can quickly gain familiarity with PyTorch, NVidia GPUs and the software stacks that optimize them (e.g. NCCL, CUDA), as well as HPC technologies such as InfiniBand, MPI, NVLink, etc. Have experience architecting, building, observing, and debugging production distributed systems. Bonus point if worked on performance-critical distributed systems. Have need

Who We Are Verkada is transforming how organizations protect their people and places with an integrated, privacy-sensitive AI-powered platform that includes solutions for video security, access control, air quality sensors, alarms, intercoms, and visitor management. We’ve got serious momentum in the market: more than 30,000 customers (including 100+ of the Fortune 500), a $5.8B valuation , more than $1 billion in annualized bookings, and backing from CapitalG, Sequoia Capital, General Catalyst, Felicis Ventures, Next47 and more. Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the center of it. You can look at all kinds of communities to see our platform’s impact in the world. It's the retailer that uses our agentic AI to deter theft before it happens. The warehouse that uses AI-powered alerts to make sure its team is protected on the floor with proper PPE. The school that’s alerted to a threat in real-time and triggers a lockdown in seconds, not minutes. We’re rapidly scaling this impact: today, more than 2 million Verkada devices are deployed across 170+ countries. About the role As an embedded security engineer on the Device Security Team, you’ll work with an amazing team of security, firmware, and backend engineers entrusted with the mission of protecting our fleet of physical security products from threats. You’ll help define the security & privacy roadmap for Verkada’s devices, build tooling and software to measure & improve security posture, and partner closely with product teams to bake secure-by-design principles into our products. What You'll Do Develop & drive security requirements for the hardware and firmware that goes onto the devices we ship to our customers to improve the security of Verkada’s products and exceed customer expectations. Build security tooling to ensure secure development best practices. Perform red team/offensive assessments against firmware &

Who We Are Verkada is transforming how organizations protect their people and places with an integrated, privacy-sensitive AI-powered platform that includes solutions for video security, access control, air quality sensors, alarms, intercoms, and visitor management. We’ve got serious momentum in the market: more than 30,000 customers (including 100+ of the Fortune 500), a $5.8B valuation , more than $1 billion in annualized bookings, and backing from CapitalG, Sequoia Capital, General Catalyst, Felicis Ventures, Next47 and more. Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the center of it. You can look at all kinds of communities to see our platform’s impact in the world. It's the retailer that uses our agentic AI to deter theft before it happens. The warehouse that uses AI-powered alerts to make sure its team is protected on the floor with proper PPE. The school that’s alerted to a threat in real-time and triggers a lockdown in seconds, not minutes. We’re rapidly scaling this impact: today, more than 2 million Verkada devices are deployed across 170+ countries. About the Role We’re growing incredibly fast, and so is our fleet of our products like cameras, access control, alarms, sensors. A QA engineer at Verkada owns the behavior of our products in the field and is responsible for keeping them running reliably - key to a company like ours! The QA Engineer, and their team of reliability engineers, verify new code releases against a set of test cases, grow the test suite, monitor devices in the field, and are responsible for rolling out new updates - in short, everything related to keeping deployed devices running smoothly. What You'll Do Define / create automated test system architecture for embedded systems like Access Control, Cameras, Sensors, Alarms etc. Take part in choosing technologies used in automated test system Together with a team build CI system, choose technology, set all things up, develop

P-939 (Position Location is open to both our Seattle & Bellevue offices.) At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. The impact you'll have: As a software engineer with a backend focus, you will work with your team to build infrastructure and products for the Databricks platform at scale. Our backend teams span many domains, from OS/container systems, to serverless infrastructure, to partner integration, and to machine learning infrastructure. Below are some example projects and the Serverless platform : Build Databricks serverless platform that powers the big data, machine learning and Gen AI workloads. Automatically improve the performance and efficiency of workloads running on the platform while also ensuring they scale to millions of machines across a multi-cloud environment. Core cloud platform : Build cutting-edge OS, container and networking technologies that power the entire Databricks infrastructure, from internal infrastructure, to serverful, and to serverless platform. Improve the security, efficiency and reliability across the fleet. Partner ecosystem : Build and grow a partner ecosystem for Databricks SQL. Build and offer a variety of toolkits to support partners and customers’ deep and seamless integrations with Databricks. Maintain and nurture productive and beneficial partnerships within the ecosystem. Notebook dataplane : Build mu

About the team The Browser Use team builds the technology that enables agents to interact with browsers across our products. Our work spans infrastructure, tooling, and user experiences, both on users’ devices and in the cloud. We partner with research to improve our models’ browser-use capabilities and with web standards bodies to shape how agents interact with the web. Our products include ChatGPT for Chrome, the ChatGPT in-app browser, and the cloud computer used in dots and ChatGPT Work. We see the browser as a universal connector. If we can enable our models to use it effectively, they can do anything. Come help us build the future of browsing! About the role We’re looking for a product-oriented engineer to build and scale our cloud computer infrastructure. Our goal is to give every one of our users access to an agent with their own computer in the cloud. Build novel solutions to problems like authentication, user takeover, and enterprise network access. You’ll help own the systems that provision, run, and manage the environments our agents use, making them reliable, responsive, and efficient as demand grows. This role combines infrastructure depth with close attention to the user experience. You’ll partner with research and engineering teams to bring new computer-use capabilities into production, working across container orchestration, backend services, and product experiences. In this role you will Build and scale infrastructure for running agent-controlled browsers and computers in the cloud. Develop services for provisioning environments, managing sessions, and coordinating their lifecycle. Improve reliability, performance, resource utilization, and observability across the fleet. Diagnose issues across Linux, containers, networking, and browser execution. Build APIs and tooling that make cloud computers easy for research and product teams to use. Work closely with research to understand emerging requirements and improve how computer use works. Develop auth

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. About the role As a Software Engineer on ML Platform at SpaceXAI, you'll build the infrastructure that turns real product usage into better models — and keeps research moving fast on large GPU fleets. ML Platform is organized into four teams. Depending on your background, you may join any of them: Telemetry — Own the collection and serving path that turns real product use into a record research can trust; without slowing the product, and under a small, explicit policy. Client-side or high-volume ingestion experience is a plus. ML Data Platform — Build the shared environments and pipeline substrate researchers extend, so new experiments don’t fork their own stack. Observability — Make it easy for researchers to start, watch, and debug their own runs. ML DevX and Systems — Shorten the path from idea to a trusted run on the research fleet. We're looking for strong distributed-systems and infrastructure engineers who want to sit next to research and ship platform primitives that move the product. We're in-person with cozy offices in North Beach, San Francisco, Palo Alto, and Manhattan, New York, complete with well-stocked libraries. What you’ll do Design, build, and operate core pla

Associate Interiors Payloads Support Engineer Company: The Boeing Company Boeing Commercial Airplanes Materials & Processes (BCA M&P) is seeking an Associate Interiors Payloads Support Engineer (Level 2) to provide M&P engineering support to the 787 Program and Interiors Responsibility Center in South Carolina (IRCSC), located in North Charleston/Ladson, SC. This role requires knowledge and/or experience with all categories of Interiors materials and processes used in aerospace. These technologies include: composites, thermoplastics, thermosets, metals, fasteners, adhesives, sealants, organic and inorganic finishes, and corrosion principles. We seek detail-oriented, curious engineers who enjoy learning across Payloads/Interiors. Candidates with experience in composites, finishes, metals, or fasteners are especially encouraged to apply. Position Responsibilities: Assist with definition of requirements for tools, equipment, materials, parts/processes used in the engineering design Support design engineers in material and process definition and selection of our Interiors components and flight deck structures Review drawings and specifications to ensure compliance with material and process requirements and objectives Understand engineering requirements and specifications to support material and process design consultation, production support, and fleet support Communicate with technical and non-technical personnel from multiple skill areas and functions to evaluate technical information and issues impacting design, production, and support of products, services, or other deliverables Continued on-the-job trainin

The Opportunity Typography is central to how ideas are communicated. If you're passionate about beautifully created design, have deep curiosity about what AI can do, and take personal responsibility for creating products that people love; then this may be the role for you. Adobe Fonts supports millions of creatives in choosing and using typefaces across fonts.adobe.com, Express, Photoshop, Illustrator, Acrobat, and more Creative Cloud platforms. Our Internal Services team provides the platform engineering and deployment backbone for all of these. We manage CI/CD, deployment approaches, the services and data layers our engineers depend on, our observability and security stance, and increasingly the agentic tools that transform how our entire organization delivers software. We're seeking a Senior Software Development Engineer to lead this exciting journey in our San Francisco location. What you'll do Own and evolve our deployment platform. Lead strategy for CI/CD, PR environments, and release safety across a mixed fleet that includes containerized services, serverless services, and static front ends. Build the foundation for AI-accelerated development. Help build our agent factory and grow our internal agentic toolkit and skill library. Ship inference applications at scale. Take greenfield services from spec to production and standardize our ML/inference footprint. Modernize our services for the AI era. Identify where an existing service is held back by its current build and lead the fix. Rethink our security posture for agentic threats. Lead how we secure autonomous agents and their tool use. Expose Adobe Fonts to the agentic ecosystem. Extend our Model Context Protocol (MCP) surface and conversational, intent-based font discovery. Work higher up the stack, too. Contribute directly to search, browse, discovery, and the customer-facing experie

Technician Address: Chennai 1 ETC Tower 200 Feet Road MCN Nagar Extension Pallavaram Ring Road Thoraipakkam Facility: TCS MAGNUM - FM Qualification: ITI Experience: 1 - 2 years Source: Sodexo India | Job Code: IJP574105

Housekeeping Address: Chennai 1 ETC Tower 200 Feet Road MCN Nagar Extension Pallavaram Ring Road Thoraipakkam Facility: TCS MAGNUM - FM Qualification: 12th Experience: 1 - 2 years Source: Sodexo India | Job Code: IJP562840

Housekeeping Address: Chennai 1 ETC Tower 200 Feet Road MCN Nagar Extension Pallavaram Ring Road Thoraipakkam Facility: TCS MAGNUM - FM Qualification: Not Specified Experience: 1 - 2 years Source: Sodexo India | Job Code: IJP542745

Housekeeping Address: Chennai 1 ETC Tower 200 Feet Road MCN Nagar Extension Pallavaram Ring Road Thoraipakkam Facility: TCS MAGNUM - FM Qualification: Not Specified Experience: 1 - 2 years Source: Sodexo India | Job Code: IJP542746