Advanced Operations Engineering Graduate Program 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. About the Team The Finance Data Science team owns the forecasting systems that power Snowflake’s revenue planning and long-term financial strategy. Our work supports corporate planning, executive decision-making, and investor reporting, and we partner closely with Product and Sales to understand customer behavior and product impact. We operate at the intersection of machine learning, statistical research, and corporate finance, building production-grade forecasting infrastructure that is foundational to how the company plans and operates. The Role As a Senior Data Scientist, you will independently lead high-impact modeling initiatives and build production-ready forecasting systems for core financial metrics. You will work on complex, open-ended problems at the intersection of machine learning and business strategy, translating real-world financial questions into rigorous, scalable models. What You’ll Do Design and implement advanced time-series and probabilistic models (e.g., hierarchical models, state-space models, Bayesian approaches, multivariate forecasting). Contribute to internal tooling and shared infrastructure that enables scalable forecasting and analytics. Establish best practices for model evaluation, backtesting, uncertainty quantification, and scenario simulat

About the Team OpenAI is building the world’s most advanced AI infrastructure ecosystem. The Site Readiness & Development team owns the upstream diligence and development work required to convert powered-land opportunities into executable infrastructure options. About the Role The Site Selection Lead sets the site-selection strategy for powered-land and greenfield/brownfield opportunities. This role defines, with cross-functional partners, what makes a site attractive, executable, and scalable, then turns that shared rubric into portfolio choices and deployment plans. Key Responsibilities Own the site-selection strategy across priority geographies, including market maps, pipeline segmentation, source refreshes, live-location tracking, and portfolio prioritization. Convene Power, Land, Development, Engineering, Construction, Environmental, Community, Commercial, Legal, and Finance partners to define the shared rubric for a high-quality site. Translate that rubric into clear screening criteria across power readiness, land control, timing, scale, cost, community risk, environmental constraints, AHJ path, budget, schedule, and counterparty credibility. Orchestrate Commercial, Legal, Finance, Power, and Development teams to shape exclusivity, initial terms, site-control strategy, funding assumptions, and the path to deployment before deeper commitment. Build a deployment plan for top candidates that identifies capacity, sequencing, capital implications, critical-path approvals, risks, owners, and stage-gate decisions. Lead conceptual site planning and test-fit screening using boundaries, map layers, buildings, substations, roads, parking, laydown, stormwater, utility corridors, acreage, and estimated load. Maintain a single decision-support view of pipeline stage, site health, power readiness, finance review, maps, project evidence, outstanding source data, owners, deadlines, and escalations. Present executive-ready advance, defer, or stop recommendations with clear

About the Team Industrial Compute is building the world's most advanced AI infrastructure. Working alongside our capital partners, engineering teams, and construction organizations, we design and deliver large-scale, mission-critical compute campuses that power the next generation of AI. Our Design organization brings together engineering, construction, and digital design to ensure facilities are coordinated, constructible, and optimized from the earliest planning phases through deployment. About the Role We are seeking a BIM Designer & Coordinator to support the planning and design of large-scale industrial and mission-critical facilities. In this role, you will develop, coordinate, and maintain multidisciplinary BIM models across Civil, Electrical, Mechanical, Architectural, and Structural disciplines, enabling early design validation, constructability reviews, equipment planning, and cross-functional coordination. You will partner closely with internal engineering teams, external design consultants, contractors, and project stakeholders to produce coordinated BIM deliverables that improve design quality, reduce project risk, and support efficient execution across Industrial Compute's global infrastructure portfolio. Key Responsibilities: Develop and maintain conceptual and schematic BIM models for large-scale industrial and MEP-intensive facilities. Coordinate BIM models across Civil, Electrical, Mechanical, Architectural, and Structural disciplines. Create and maintain federated models used for design reviews, spatial coordination, constructability analysis, and clash detection. Model major building systems including equipment layouts, utility corridors, electrical rooms, mechanical rooms, structural framing, site infrastructure, and architectural constraints. Coordinate equipment clearances, maintenance access, routing zones, shafts, risers, utility entrances, and major MEP pathways. Translate engineering sketches, basis-of-design documents, equipment lists

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. We are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect -- for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models. Improve AI compilers to hide communications or perform automatic fusion. Conduct in-depth AI workload performance characterization on multi-GPU clusters. Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads. Author

About the Team The ChatGPT organization at OpenAI supports our mission by bringing advanced AI capabilities to hundreds of millions of users worldwide. The Image Generation team is responsible for one of the fastest-growing experiences in ChatGPT, enabling users to create, edit, and transform images through natural language. Recent advances in our multimodal image models have dramatically improved image quality, instruction following, editing precision, consistency, and text rendering, unlocking entirely new creative and professional workflows. We work at the intersection of research, infrastructure, and product to build the systems that power image generation at global scale. Our team partners closely with researchers, product engineers, designers, and platform teams to bring state-of-the-art image capabilities to millions of users while continuously pushing the boundaries of what AI-powered creation can do. About the Role We are looking for an experienced Backend Engineer to join the Image Generation team and help build the systems that power image creation and editing across ChatGPT. You'll work on the core backend infrastructure that enables users to generate, edit, and iterate on visual content using cutting-edge multimodal AI models. This includes building highly scalable services, orchestration systems, APIs, storage platforms, and distributed infrastructure that support billions of image generations and editing workflows. You'll partner closely with product, research, and mobile teams to transform breakthrough AI capabilities into reliable, performant experiences used by millions around the world. In this role, you will: Design, build, and operate backend systems that power image generation and image editing experiences in ChatGPT. Develop scalable APIs, services, and infrastructure that support multimodal AI workflows. Optimize reliability, latency, throughput, and cost across large-scale distributed systems. Partner with researchers to productionize new im

About the Team The ChatGPT organization at OpenAI supports our mission by bringing advanced AI capabilities to hundreds of millions of users worldwide. The Image Generation team is responsible for one of the fastest-growing experiences in ChatGPT, enabling users to create, edit, and transform images through natural language. Recent breakthroughs in multimodal AI have dramatically improved image quality, instruction following, editing precision, consistency, and text rendering. We're building the systems and experiences that turn these research advances into products used daily by creators, professionals, businesses, and consumers around the world. Our team sits at the intersection of research, product, design, and infrastructure. We work closely with model researchers, mobile engineers, frontend engineers, and platform teams to build intuitive experiences and scalable systems that power image generation at global scale. Whether users are creating marketing assets, visualizing ideas, editing photos, designing products, or simply exploring their creativity, our goal is to make visual creation feel as natural as having a conversation. About the Role We are looking for an experienced Full Stack Engineer to join the Image Generation team and help shape the future of AI-powered visual creation. In this role, you'll own features end-to-end across both frontend and backend systems, building the experiences that enable users to generate, edit, organize, and interact with images inside ChatGPT. You'll work across the entire stack—from highly interactive user interfaces and real-time workflows to backend services, APIs, orchestration systems, and data infrastructure. This role is ideal for engineers who enjoy moving fluidly between product development and systems engineering, collaborating closely with design, product, and research teams to rapidly bring new AI capabilities to users. You'll help define entirely new interaction paradigms as multimodal AI continues to evolve. In

About the Team OpenAI’s Inference team powers the deployment of our most advanced models - including our GPT models, 4o Image Generation, and Whisper - across a variety of platforms. Our work ensures these models are available, performant, and scalable in production, and we partner closely with Research to bring the next generation of models into the world. We're a small, fast-moving team of engineers focused on delivering a world-class developer experience while pushing the boundaries of what AI can do. We’re expanding into multimodal inference, building the infrastructure needed to serve models that handle image, audio, and other non-text modalities. These workloads are inherently more heterogeneous and experimental, involving diverse model sizes and interactions, more complex input/output formats, and tighter coordination with product and research. About the Role We’re looking for a software engineer to help us serve OpenAI’s multimodal models at scale. You’ll be part of a small team responsible for building reliable, high-performance infrastructure for serving real-time audio, image, and other MM workloads in production. This work is inherently cross-functional: you’ll collaborate directly with researchers training these models and with product teams defining new modalities of interaction. You'll build and optimize the systems that let users generate speech, understand images, and interact with models in ways far beyond text. In this role, you will: Design and implement inference infrastructure for large-scale multimodal models. Optimize systems for high-throughput, low-latency delivery of image and audio inputs and outputs. Enable experimental research workflows to transition into reliable production services. Collaborate closely with researchers, infra teams, and product engineers to deploy state-of-the-art capabilities. Contribute to system-level improvements including GPU utilization, tensor parallelism, and hardware abstraction layers. You might thrive in t

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions optimized for advanced AI workloads. We collaborate across research, software, and external hardware partners to design and deploy next-generation AI systems at scale. Our team works closely with silicon vendors and system partners to evaluate emerging technologies, validate performance characteristics, and ensure that hardware capabilities translate effectively to real-world AI workloads. About the Role We are seeking a 3P Hardware Architecture Expert with deep expertise in GPU and accelerator architectures to engage directly with silicon vendors and guide hardware decisions for AI infrastructure. In this role, you will evaluate architectural tradeoffs across compute, memory, and interconnect systems, translating vendor specifications into real-world workload impact. You will play a critical role in early silicon evaluation, benchmarking, and performance validation, helping ensure that next-generation hardware meets the needs of our workloads. This role is highly hands-on and requires both deep technical understanding and the ability to engage at a high level with partners such as NVIDIA and AMD on architectural direction and design tradeoffs. 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. Key Responsibilities Engage deeply with silicon vendors (e.g NVIDIA & AMD) on GPU and accelerator architecture tradeoffs. Analyze and interpret performance, power, and efficiency characteristics of next-generation hardware. Translate vendor specifications into expected real-world performance for AI workloads. Evaluate architectural aspects including: compute throughput and utilization memory systems (HBM, cache hierarchies, bandwidth constraints) data types and precision tradeoffs (FP16, BF16, FP8, etc.) interconnect and scaling behavior. Run benchmarks and profiling to validate hardware performance a

About the Team OpenAI’s Infrastructure organization builds and evaluates the systems that power advanced AI workloads. We work closely with hardware, modeling, and architecture teams to ensure that new platforms deliver real-world performance aligned with workload needs. Our team focuses on understanding workload behavior across evolving hardware platforms—bridging the gap between theoretical capability and observed system performance. About the Role We are seeking a Workload Porting & Performance Engineer to evaluate new hardware platforms by porting benchmarks and real-world workloads, analyzing performance, and identifying system bottlenecks. In this role, you will bring up workloads on new systems, characterize performance behavior, and adapt workloads to better utilize hardware capabilities. You will play a critical role in validating new platforms and ensuring that performance aligns with expectations across compute, memory, and networking subsystems. This role requires strong hands-on experience with performance analysis, workload optimization, and system-level debugging across hardware and software boundaries. 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. Key Responsibilities Port and enable benchmarks and real-world workloads on new hardware platforms. Evaluate system performance across compute, memory, storage, and networking subsystems. Identify and analyze performance bottlenecks and inefficiencies. Adapt and optimize workloads to better utilize hardware capabilities. Develop and run performance experiments and profiling workflows. Compare expected vs. observed performance and provide feedback to: hardware architecture teams performance modeling teams system and software engineers. Debug issues across the stack, including software, runtime, and hardware interactions. Provide actionable insights to guide platform readiness and deployment decisions. Qualifications E

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that deliver the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing some of the world’s most transformative technologies. Our new AI Engineering Campus in Austin will play a central role in building the future of AI computing. The Opportunity We are seeking a system validation engineering intern to help drive server blade and rack validation efforts for next-generation AI infrastructure hardware systems. This role focuses on post-silicon system validation across the full lifecycle of server hardware systems, ensuring functional and performance meets product objectives. You will help drive end-to-end blade and rack validation including development, execution, and debug while collaborating across silicon, firmware, systems, and platform teams. The Blade and Rack Validation team is responsible for ensuring system readiness and quality at scale. The team works cross-functionally with firmware, silicon, and system engineering teams to validate complex AI compute platforms. Type: 12-week summer internship Timing: May - August (exact dates to be confirmed) Commitment: Full-time What You’ll Do Help drive and execute post-silicon validation goals of AI compute blades and racks including testcase planning, development, and automation Help drive validation testcase execution and system debug against program achievements and report validation progress and risks. Drive provisioning and integration of system components (SoC FW, BMC, RMC, OS) for rack-level readiness Triage test failures, collect debug data, and collaborate on root cause analysis. Track validation coverage and continuously improve test processes and infrastructure. What You’ll Bring Working towards a Bachelor's

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that provide the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing transformative technologies. Our AI Engineering Campus in Austin plays an important role in building the hardware platforms that support the next generation of AI systems. The Opportunity As a Systems Engineering Intern, you will contribute to projects that combine hardware, firmware, and software engineering for advanced AI compute platforms. You will work with experienced engineers on subsystem design, laboratory testing, system validation, automation, and performance analysis. The internship provides hands-on experience with modern hardware development and system-level engineering. You will own clearly defined technical tasks with guidance from the team and document your methods, results, and conclusions. What You Will Do Support the design and testing of CPU and high-speed input and output subsystems for advanced compute platforms. Run laboratory tests and measurements to help evaluate performance, power, signal behavior, and reliability. Contribute to system-level validation by creating scripts and tools that streamline testing, data collection, and analysis. Explore emerging input and output technologies, including PCIe 6.0 and 800G Ethernet, and learn how they support advanced computing workloads. Assist with investigations into platform power, cooling, and energy efficiency, including liquid-cooling systems for high-performance processors. Use power meters, oscilloscopes, logic analyzers, or comparable lab equipment under appropriate supervision. Analyze test results, identify unexpected behavior, and work with engineers to reproduce and investigate issues. Collaborate across hardware, firmware, software, m

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that provide the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing transformative technologies. Our AI Engineering Campus in Austin plays an important role in building the hardware platforms that support the next generation of AI systems. The Opportunity We are looking for a recent graduate or early-career engineer to join the Hardware Platform Development team as a Graduate Systems Engineer. You will contribute to the design, integration, validation, and performance analysis of advanced AI compute platforms. You will work with experienced hardware, firmware, software, mechanical, thermal, and systems engineers throughout the development lifecycle. The role combines subsystem engineering, hands-on laboratory work, test automation, data analysis, troubleshooting, and clear technical documentation. Start: September, 2027 Location: Austin, Texas, USA What You Will Do Contribute to the design, integration, and testing of CPU and high-speed input and output subsystems for advanced compute platforms. Take ownership of defined engineering tasks from requirements and test planning through execution, analysis, and technical review. Develop system-level validation plans, procedures, scripts, and tools that improve test coverage, repeatability, data collection, and analysis. Evaluate platform performance, power, signal behavior, reliability, and interoperability using laboratory measurements and system data. Investigate emerging input and output technologies, including PCIe 6.0 and 800G Ethernet, and assess their use in advanced computing systems. Support platform power, cooling, and energy-efficiency investigations, including liquid-cooling systems for high-performance processor

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that deliver the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing some of the world’s most transformative technologies. Our new AI Engineering Campus in Austin will play a central role in building the future of AI computing. The Opportunity As a Graduate Performance Engineer, you will contribute to the design, integration, bring-up, and validation of complex server- and rack-level performance of elaborate, large-scale systems. You will work alongside experienced engineers, software developer, and cross-functional partners while building practical skills in component, system and scale up/out performance optimization and design. Start: September, 2027 Location: Austin, Texas, USA What You’ll Do Support the design, peer review, bring-up, and debug of complex server- and rack-level systems. Assist with modeling, design and evaluation of the complete software and hardware stack identifying performance bottlenecks, possible solutions and testing those outcomes. Collaborate with many different teams across both hardware and software development and testing. What You’ll Bring A bachelor’s or master’s degree in electrical engineering, computer engineering, or a related discipline, completed before the role’s start date. Equivalent relevant education or practical experience will also be considered. Foundational knowledge of software development, hardware architecture and general understanding of performance implications. Hands-on experience gained through coursework, laboratories, internships, research, student projects, or personal projects. Ability to analyze technical problems, document your work, communicate clearly, and collaborate effectively. Curiosity, sound engineering judgment, a

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that provide the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing transformative technologies. Our AI Engineering Campus in Austin plays an important role in building the hardware platforms that support the next generation of AI systems. The Opportunity We are looking for a recent graduate or early-career engineer to join the Mech/Thermal Platform team as a Graduate Mechanical Engineer. You will contribute to the mechanical design, thermal validation, and verification of advanced AI hardware and data center systems. You will work with experienced mechanical, thermal, hardware, and systems engineers throughout the development lifecycle. The role combines 3D computer-aided design, prototype evaluation, lab testing, data analysis, troubleshooting, and clear engineering documentation. What You Will Do Create and update mechanical parts, assemblies, and drawings using Creo or comparable 3D CAD software. Take ownership of defined mechanical design tasks from requirements and concepts through detailed design, review, release, and verification. Apply mechanical design, materials, manufacturing, heat transfer, and thermodynamics principles to engineering decisions. Develop mechanical and thermal test plans and procedures for prototypes and development systems. Set up and operate laboratory equipment, collect accurate data, analyze results, and document conclusions. Evaluate prototypes and identify mechanical, thermal, assembly, or manufacturability issues. Support design verification, troubleshooting, root-cause analysis, and implementation of verified design improvements. Maintain accurate engineering documentation, including design notes, drawings, test procedures, results, and change r

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that deliver the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing some of the world’s most transformative technologies. Our new AI Engineering Campus in Austin will play a central role in building the future of AI computing. The Opportunity As a Mechanical Engineering Intern, you will contribute to the mechanical design and thermal validation of advanced AI hardware. Working alongside experienced mechanical and thermal engineers, you will gain hands-on experience with 3D computer-aided design (CAD), laboratory setup, test development, prototype evaluation, and engineering documentation. Type: 12-week summer internship Timing: May - August (exact dates to be confirmed) Commitment: Full-time What You’ll Do Contribute to mechanical design activities using Creo or comparable 3D CAD software, including part modeling, assemblies, drawings, and design updates under the guidance of experienced engineers. Work with the thermal engineering team to develop test procedures and help set up laboratory capabilities for evaluating AI hardware. Support thermal and mechanical testing using appropriate laboratory equipment; collect, organize, and analyze test data. Assist the mechanical and thermal design teams with prototype evaluation, troubleshooting, design verification, and documentation of findings. Collaborate with cross-functional engineering partners, communicate progress and issues clearly, and follow applicable laboratory and safety procedures. What You’ll Bring Current enrollment in a bachelor's, master's, or doctoral program in mechanical engineering or a related discipline during the internship. Students in other disciplines with relevant mechanical engineering exper