Fleet Operations Associate in United States

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Staff Software Engineer - Container Platform (Menlo Park) About the Role We build the foundational container platform that runs Snowflake's production, AI/ML, and CI workloads across AWS, Azure, and GCP, including a rapidly growing AI/ML footprint. Hundreds of large Kubernetes clusters under management and growing. The work is to make that fleet reliable, automated, and invisible to the thousands of engineers building on top of it. This is a staff-level role on a senior, high-performing platform team. You'll own hard problems end to end, drive technical direction across teams, and build the automation and platform abstractions that make operating at this scale sustainable. There is significant unsolved work ahead: improving the developer experience for thousands of internal engineers and continuing to scale the platform to meet Snowflake's growth. What You'll Do Own the design and delivery of large, complex platform initiatives spanning cluster lifecycle management, multi-cloud automation, and internal developer tooling. Identify and drive cross-team technical improvements across the platform, from architecture through adoption. Make and defend architectural trade-offs grounded in reliability, scalability, and operational reality. Act as a technical anchor for the team, dev

VTS is the category leader in commercial real estate technology with more than 13 billion square feet managed on our platform globally. Every account in your book represents an opportunity to expand how some of the largest owners and operators in the industry leverage technology to modernize their portfolios. As an Account Manager, you will work directly with leadership while helping drive the next phase of growth at VTS. You will own expansion revenue across a portfolio of 60 to 80 SMB and lower mid market commercial real estate accounts. Your job is simple: generate and close net new revenue within your book. That means identifying whitespace, creating urgency, and running multiple deal cycles simultaneously, not waiting for opportunities to come to you. This is not a support role. Renewals and adoption are handled separately. You own the commercial motion including upsells, cross sells, and new product expansion, with a direct quota and meaningful upside for top performers. Here’s what you can expect as an Account Manager: Proactively identify expansion opportunities across your book using product usage data, account signals, and direct customer conversations. Run 30 to 60 day deal cycles across multiple accounts simultaneously. Build relationships with decision makers and navigate 1 to 3 stakeholder buying groups to close opportunities. Maintain a disciplined pipeline with accurate forecasting and clear next steps on every active deal. Partner closely with Customer Success and Sales while maintaining ownership of the commercial opportunity. Create urgency and momentum across active deals instead of reacting to inbound demand. What makes you a great fit? 2-4 years in a quota carrying B2B SaaS role across account management, SMB sales, or expansion focused customer roles. Demonstrated success sourcing and closing expansion revenue independently. Experience managing a high volume book of business with strong organizat

What we’re doing isn’t easy, but nothing worth doing ever is. 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. Join our mission-driven, venture-backed team as we build out current and future generations of humanoid robots. Field-based · ~75% travel · Preference for candidates near a major airport About the Role The Client Success Manager owns the health, performance, and growth of a hospital or territory of hospital partners running Moxi robot fleets. You are both the executive relationship owner and the operator behind the numbers: you run leadership check-ins and quarterly business reviews, translate utilization data into a clear story about value delivered, and drive the projects that resolve issues and lift site performance. Priorities shift, sites behave differently, and the playbook is still being written. The CSMs who thrive here make good decisions with incomplete information and move fast without losing rigor. What You'll Be Doing Own executive relationships and the value narrative Serve as the trusted executive contact for each hospital — C-suite sponsors, nursing leadership, and operational stakeholders. Lead recurring leadership check-ins and quarterly business reviews: set the agenda, build the deck, present performance against goals, and close with documented decisions, owners, and next steps. Communicate Moxi's value in each stakeholder's terms — clinical hours returned, delivery volume, staff satisfaction, cost avoidance — continuously, not just at renewal. Use data to drive better outcomes Monitor utilization, adoption, and reliability data across your territory; know each site's baseline, trends, and outliers. Diagnose why a site underperforms, run the intervention, and measure whether it worked. Set and track site-level performance targets with partners, and report on progress h

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re looking for a Recruiting Coordinator to help create a seamless, welcoming, and well-organized interview experience for every candidate who engages with our team. You’ll work closely with our recruiters to coordinate both virtual and in-person interviews, support executive involvement when needed, and ensure candidates have everything they need during throughout their interview process. This role is ideal for someone who thrives on operational excellence, loves solving logistics problems on the fly, and brings both warmth and precision to every interaction. RESPONSIBILITIES Work closely with recruiters and hiring managers to coordinate interview loops and debriefs for candidates and the internal team members conducting interviews Ensure every candidate has a smooth, well-communicated, and positive experience Manage logistics for onsite interviews, including candidate arrival and workspace setup Proactively identify and solve day-of issues, including last-minute changes or scheduling conflicts Communicate clearly and promptly with candidates and internal teams about interview logistics and updates REQUIREMENTS 1+ year of recruiting or HR experience Detail-oriented and operationally strong—you know how to keep things moving Clear and professional written and verbal communication skills Personable and warm—you're great at making candidates feel welcome and supported Ability to think on your feet and respond to

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake runs large scale cloud infrastructure to deliver its own service — production and internal deployments, Kubernetes fleets, CI/CD, etc. Our cloud spend is in billions of dollars per year. The Cloud Efficiency team builds a unified, self-serve cloud efficiency platform along with AI skills and agents that makes spend observable, attributable, governable while driving recommendations and optimization of our cloud spend. AS A SOFTWARE ENGINEER AT SNOWFLAKE YOU WILL: Design, develop, and maintain scalable platform for resource ownership registry, usage attribution, utilization measurement, and cost modeling. Build AI agents, tools and automation to enhance system monitoring, alerting, and root cause analysis. Improve and optimize data ingestion, storage, and query efficiency for cloud utilization, cost and efficiency data at scale. Collaborate with teams across Snowflake to understand attribution and observability needs and implement solutions that improve operational visibility. Contribute to open-source and industry best practices in monitoring and distributed systems monitoring. Ensure high availability, reliability, and performance of team-managed platforms by participating in on-call rotations and incident management. Partner with Finance, Product and Engineering

NA Fleet Management (Nashville, TN) — Nashville, Tennessee, United States. Apply via Workday.

This role will support the fleet infrastructure team at OpenAI. The fleet team focuses on running the world’s largest, most reliable, and frictionless GPU fleet to support OpenAI’s general purpose model training and deployment. Work on this team ranges from Maximizing GPUs doing useful work by building user-friendly scheduling and quota systems Running a reliable and low maintenance platform by building push-button automation for kubernetes cluster provisioning and upgrades Supporting research workflows with service frameworks and deployment systems Ensuring fast model startup times though high performance snapshot delivery across blob storage down to hardware caching Much more! About the Role As an engineer within Fleet infrastructure, you will design, write, deploy, and operate infrastructure systems for model deployment and training on one of the world’s largest GPU fleet. The scale is immense, the timelines are tight, and the organization is moving fast; this is an opportunity to shape a critical system in support of OpenAI's mission to advance AI capabilities responsibly. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, implement and operate components of our compute fleet including job scheduling, cluster management, snapshot delivery, and CI/CD systems. Interface with researchers and product teams to understand workload requirements Collaborate with hardware, infrastructure, and business teams to provide a high utilization and high reliability service You might thrive in this role if you: Have experience with hyperscale compute systems Possess strong programming skills Have experience working in public clouds (especially Azure) Have experience working in Kubernetes Execution focused mentality paired with a rigorous focus on user requirements As a bonus, have an understanding of AI/ML workloads About OpenAI OpenAI is an AI resea

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 We’re looking for a Rack Power Engineer with deep expertise in high-power conversion and distribution to design, qualify, and support power systems for AI supercomputers. You will own rack power solutions—including power shelves, AC/DC rectifiers, power supply units (PSUs), power management controllers (PMCs), and high-current distribution—from requirements and supplier development through deployment. You will also monitor fleet rack power health, lead debugging and root-cause investigations, and drive improvements into hardware, firmware, and qualification coverage. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own rack power architecture and requirements for high-power AI supercomputing systems, including power budgets, AC input interfaces, DC distribution, redundancy, efficiency, serviceability, and integration with data center infrastructure. Drive the design and supplier development of power shelves, rectifiers, PSUs, PMCs, busbars, connectors, and protection circuits. Review electrical designs and control behavior, and evaluate performance, cost, reliability, and availability trade-offs. Define and execute component, shelf, and rack qualification plans covering load transients, current sharing, hot-swap, startup and shutdown, redundancy failover, fault protection and recovery, thermal limits, and AC disturbances and ride-through

About the Team The Fleet team builds core components to enable productive research from small to state of the art scale across OpenAI, with the goal of accelerating progress towards AGI. We frequently collaborate with other teams to speed up the development of new state-of-the-art capabilities. About the Role As we scale up with more researchers and engineers joining OpenAI, we seek a pragmatic and passionate engineer with a strong focus on the development experience for both engineers and scientists. In this role, you will be responsible for building and maintaining systems that allow our research + engineering organization to iteratively develop, test, and deploy new features reliably, with high velocity, and with a frictionless and fast development cycle. You will help oversee and drive to the vision of how we should build, test and deploy software. You will drive the design of our continuous integration pipelines, testing infrastructure, training and support around our build system. Our current environment relies heavily on Python, Rust, and C++, which you will take ownership of and strive to transform into a state of the art development experience for research. Ultimately, your role will be to provide the necessary tools and metrics to support our fast-paced culture and ensure a stable, scalable platform for growth, while also fostering a seamless and low friction experience for OpenAI’s research. This role is based in San Francisco, CA. For a San Francisco role, we use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. You might thrive in this role if you: Have supported large monorepo development and deployment before Are a proficient Python programmer working in large monorepos Are proficient with Docker and Kubernetes Experienced in CI/CD About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boun

About the Team The compute infrastructure team runs the GPU fleet and large-scale compute clusters that serve the models backing ChatGPT and the API, while also supporting training workloads for our next generation models. We operate a large, modern GPU fleet and provide a unified platform for other OpenAI teams to seamlessly run production Applied AI and Research training workloads. 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 You will be part of an engineer-first TPM team as a Technical Program Manager for Compute Infrastructure who owns the end-to-end delivery of large-scale GPU clusters, partnering with engineers to bring clusters online across external providers and partners. You’ll run a broad, parallel portfolio spanning hardware, networking, power, and cooling—driving execution, risk management, and crisp alignment from working teams through leadership to deliver production-ready capacity at scale. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Lead end-to-end delivery of both New Compute SKUs and large-scale GPU clusters across an external partner ecosystem while supporting capacity planning for training and inference. Ability to contextually drive multi-threaded bring-up programs spanning hardware, networking, power, and cooling—owning plans, dependencies, and critical paths. Interface with chip providers to derisk long-term onboarding to new hardware platforms by working across kernels, comms, hardware, and scheduling engineering teams. Build and operationalize program mechanisms (roadmaps, milestones, risk registers, runbooks) that make delivery predictable at massive scale. Partner with engineering to improve cluster turn-up reliability, repeatability, and automation

About the Team Our team analyzes inference stack performance across the application, model, and fleet layers to identify bottlenecks and drive faster, cheaper inference. We combine systems profiling, benchmarking, and analysis to understand where time and cost are spent, then turn that understanding into performance optimizations and models that project performance and capacity needs for future launches. About the Role In this role, you will model inference performance across application, model, and fleet layers with higher fidelity. You will build cost-to-serve estimates from microbenchmarks and create tools that help cross-functional teams reason about latency, capacity, utilization, and cost tradeoffs. In this role, you will Build and refine performance models that translate microbenchmark results into cost-to-serve estimates. Analyze inference workloads end to end across applications, models, and fleet infrastructure. Enhance tooling to identify bottlenecks across layers for latency and throughput. Partner with other teams to turn performance insights into concrete improvements and project how future changes affect inference. You might thrive in this role if you: Enjoy reasoning from first principles about distributed systems, model inference, and hardware efficiency. Are comfortable working across abstraction layers, from application behavior to kernels, accelerators, networking, and fleet scheduling. Have deep expertise with performance profiling, benchmarking, analysis, and optimization. Enjoy collaborating with engineering and research teams to improve real production systems. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve o

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. In this part-time position, you will work 20 hours per week, to including every other weekend. You will participate in a holiday rotation. Availability to work East Coast hours is required. Position Summary The MinuteClinic Support Coordinator is responsible for managing nationwide callouts, processing Workbrain payroll corrections for the fleet, and performing various administrative tasks. This role requires timely handling of callouts and an understanding of the dynamic work environment and unique staffing needs of retail health clinics. The Support Coordinator will collaborate with their direct supervisor, regional coordinators, and field leaders to review and analyze Workbrain payroll corrections related to staffing and scheduling. This position requires weekend coverage and scheduling flexibility to work part-time (20 hours per week) across 4–5 days, with shifts varying between 6:00 AM and 9:00 PM Eastern Time. Required Qualifications Minimum of 1 year of experience in workforce scheduling or a related field. High School diploma or GED equivalent. Preferred Qualifications Knowledge of workforce scheduling practices. Strong attention to detail and ability to meet deadlines. Critical thinking and problem-solving skills. Excellent custom

NVIDIA DGX Cloud is an AI Factory designed to power the next generation of AI and industrial-scale breakthroughs. As a Principal Engineer for Security Architecture, within our Security Engineering organization, you will own a core security domain of the AI factory: the architecture, the paved road that delivers it, and much of the code underneath. You will hold the security design bar across DGX Cloud from inside the teams doing the building, and this is a founding seat on a new team. Security Engineering is a new organization at DGX Cloud, accountable for the security outcome of the platform, and Security Architecture is the function inside it that holds the design bar. Security here is fleet horizontal and stack vertical, so your work will cross every DGX Cloud engineering organization: you will embed with the teams building GPU clusters, control planes, and services, join their designs as a participant rather than an approver, and leave behind systems in which an entire class of risk is no longer possible. There is no architecture review board here and no approval queue. You are a senior IC with deep security domain knowledge, and the security bar holds because you helped set it and then helped ship it. What You Will Be Doing: Own a Security Domain End to End: Take architectural ownership of a core domain of DGX Cloud security, from the design through the system running in production. That could be tenant and GPU workload isolation, workload identity, infrastructure and network, supply-chain provenance, hardened baselines and patching, or deploy-time policy and admission control. Embed with the Teams Building It: Join the design early, write the code, and help land it. The posture is not "you did this wrong." It is "here are the considerations we need to meet, I will help, let's go to work." Build Paved Roads, Not

NVIDIA DGX Cloud is an AI Factory designed to power the next generation of AI and industrial-scale breakthroughs. As the Distinguished Engineer for Security Architecture, within our Security Engineering organization, you will set the security design bar for an AI factory of hundreds of thousands of GPUs, and then build against it alongside the teams. This is the founding architecture seat in a new organization. Security Engineering is a new organization at DGX Cloud, accountable for the security outcome of the platform, and this is the architecture function inside it. You will define the security design standard for DGX Cloud, a bar that sits above the company floor, and hold it from inside the teams doing the building. Security here is fleet horizontal and stack vertical, so your scope runs from the hardware root of trust and the hardened baseline, through tenancy and GPU workload isolation, to the services and APIs built on top, across every DGX Cloud engineering organization. A small team of Principal Engineers will report to you and hold the bar at domain depth. This is still a hands-on seat, and you stay in the design with them. You will also serve as DGX Cloud's technical interface into NVIDIA's central security organization. There is no architecture review board here and no approval queue; the bar holds because the strongest security engineers in the room helped set it and helped ship it. What You Will Be Doing: Set the DGX Cloud Security Bar: Own the security design standard across DGX Cloud (tenancy, GPU workloads, identity, supply chain, and isolation) and make it concrete. Reference architectures, golden paths, and requirements engineers can actually build against, not a policy library. Hold the Bar by Building: Embed with engineering teams on real work: join the design, learn the code, help ship the thing rather than grade it afterward.

Job Title Sales, Strategic Accounts Director - Image Guided Therapy Systems (Southeast/Mid-Atlantic) Job Description The Director of IGT Strategic Accounts will work with 2 IGTS Districts and be responsible for order and revenue growth at a targeted set of named accounts. Your primary responsibilities will be to act strategically and grow Philips Marketshare by focusing on: executing fleet replacement plans of Philips Install Base accelerating competitive replacements at accounts where Philips is not installed (red accounts). In this role, you will work closely with the Philips IGT Sales and Marketing teams, you will build deep customer relationships at multiple touchpoints throughout your assigned health systems, all while developing and deploying strategies to solve interesting hospital challenges to help IGT continue to win. Your role Deliver agreed-upon growth in targeted accounts, and contribute to the overall sales results of the covered districts. Actively manage, monitor and continually improve the team’s overall sales process to ensure a successful productivity ramp in order to exceed revenue and commercial goals. Analyze and quantify equipment replacement potential at targeted accounts, assess regional market conditions, and use this to create and execute strategies to help grow Philips share Partner with CADs and ECEs to relentlessly assess and build out IDN and GPO sales strategies that help the district grow Philips IB or replace competitive IB Track and analyze customer performance to identify positive or negative trends, all while looking for opportunities to find mutually beneficial areas for growth. Able to quickly digest data, identify trends, and turn them into proactive strategies Ability to both work with and lead the IGT field sales teams in a matrix environ