Workload Porting And Performance Engineer 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 Data Scientist, Finance About the Team The Finance Data Science team builds the forecasting and decision systems that power Snowflake's financial planning, operating cadence, and long-term strategy. Our work informs executive decision-making, product and go-to-market priorities, resource allocation, pricing, and cross-functional decisions across Finance, Product, Sales, and Data Science. We are expanding a driver-based revenue modeling platform that translates product and workload activity into trusted financial outcomes. The program began with one product category and will scale a common modeling and publishing framework across Snowflake's product categories. The models are highly visible, refreshed frequently, and designed for self-service scenario planning and business reviews. The Role We are hiring a Staff Data Scientist to lead the next phase of Snowflake's driver-based revenue modeling program. This role is not just about building models. It is about creating reliable, explainable, production-grade decision systems that connect upstream business and product levers to revenue outcomes. You will own high-impact, open-ended problems spanning driver identification, revenue decomposition, leading indicators, cohort and use-case modeling, scenario analysis, and multi

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 is redefining how enterprises bring data, applications, and AI together. As autonomous workflows begin taking actions on behalf of users, identity has officially become the new security perimeter. Every single interaction—whether initiated by a human, an application, a workload, or an AI agent—must be continuously authenticated, authorized, and governed. To unlock this next generation of enterprise software, Snowflake requires an identity platform that extends far beyond traditional workforce authentication to seamlessly support machine identities, fine-grained delegation, and policy-driven access at cloud scale. We are looking for a hands-on, high-impact Product Leader to define and build this foundational trust layer. Operating at a highly strategic intersection of product, engineering, partnerships, and executive-level customer engagement , you will own the core infrastructure that allows complex enterprise systems to securely interact, reason over sensitive data, and safely execute actions. AS A PRINCIPAL PRODUCT MANAGER AT SNOWFLAKE, YOU WILL : Set Portfolio Strategy: Own and define the long-term product strategy and roadmap for Snowflake’s IAM ecosystem, factoring in market-shifting competitive trends and technical evolutions. Build for AI era: Architect IAM

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. We are seeking experienced professionals with a strong background in Artificial Intelligence, Machine Learning, and Cloud Architecture to join our Services Delivery team to help create exciting new offerings and capabilities for our customers! In this strategic role, you will help customers expand their use of the Snowflake Data Cloud to bring AI/ML pipelines from ideation to full production. Leveraging Snowflake’s native features and extensive partner ecosystem, you will advise clients on best practices for scaling production-ready workloads. You will design tailored AI/ML solutions, coordinate closely with customer teams and Systems Integrators, and provide the technical leadership and oversight needed to ensure successful outcomes. AS A SR. SOLUTIONS ARCHITECT AT SNOWFLAKE, YOU WILL: Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload and provide customers with best practices given Snowflakes technology stack. Work with customers to understand their AI/ML use case, discover key requirements, and architect a Snowflake-centric solution to be delivered by Services Delivery. Understand how to build, deploy and AI and ML pipelines using Snowflake features and/or Snowflake ecosystem based on customer requirements. Work hands-on where needed usin

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 financial planning, operating cadence, and long-term strategy. Our work informs executive decision-making, corporate planning, investor reporting, and cross-functional decisions across Finance, Sales, and Product. We build and operate production forecasting systems for Snowflake’s core money-in metrics, with a particular focus on revenue and bookings in a consumption-based business. Our forecasts are highly visible, widely used, and foundational to how the company plans and operates. This is a high-trust team operating at the intersection of statistical modeling, production systems, and financial decision-making. The Role We are hiring a Senior Applied Scientist to own and advance mission-critical forecasting systems used across the company. This role is not just about building models. It is about developing reliable, explainable, production-grade forecasting systems that leaders can trust to make decisions. You will work on high-impact, open-ended problems involving revenue forecasting, customer consumption behavior, workload ramps, renewals, and other leading indicators that feed Snowflake’s broader financial planning processes. You will partner closely with Finance, Sales, Pr

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. At the center of the data cloud is the Snowflake Database Engineering team. We are responsible for building the core query engine used to process the massive amounts of diverse data managed by our customers. A core part of the Database Engineering group is the Query Language team which is responsible for designing, developing, and maintaining core SQL features, including advanced analytics, scripting, and the developer experience. We are seeking a Senior Engineering Manager to own and drive the effort to build core database capabilities to serve agentic workloads. You'll set the technical direction, build and grow the team behind it, and shape how the core engine and the SQL language evolve to serve this new class of workload. It's a rare chance to lead a foundational bet at the exact moment the industry is racing to solve it, with the scale, customer base, and platform to make your work matter to millions of queries a day. If you want your fingerprints on how the world's data platforms adapt to the age of AI agents, this is one of the best seats in the industry. AS A SENIOR ENGINEERING MANAGER AT SNOWFLAKE, YOU WILL BE EXPECTED TO: Drive the evolution of core database and SQL capabilities to serve emerging AI and agentic workloads alongside traditional analytics Lead and g

Datadog's integrations are the connective tissue between our platform and the technologies our customers run in the real world. As a Sr. PM on the Agent Integrations team, you will own the vision, prioritization, and execution for 100+ integrations that run directly inside the Datadog Agent from foundational infrastructure (MySQL, Kafka, Kubernetes) to the rapidly growing landscape of self-hosted AI and on-premise enterprise technologies. This is a high-impact, breadth-first role at the intersection of infrastructure observability and the frontier of AI-native workloads. At Datadog, we place value in our office culture; the relationships it builds, the creativity it brings, and the collaboration of being together. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Own the Agent Integrations roadmap. Determine which new integrations to build and which existing ones to improve, balancing customer demand, business impact, and engineering capacity across a catalog of 100+ technologies. Drive the expanding AI integration surface. Lead product strategy for self-hosted AI workloads, including LLM inference frameworks (e.g., Hugging Face TGI, BentoML), AI agents, MCP servers, and model orchestration tools, so Datadog customers can monitor every layer of their AI stack. Expand on-prem and hybrid coverage. Prioritize and execute new integrations for on-prem technologies including storage systems, HPC schedulers, network devices, and legacy enterprise platforms where customers run critical workloads. Build observability for ERP systems. Define and drive Datadog's strategy for monitoring enterprise ERP platforms (SAP, Oracle EBS/Fusion, Microsoft Dynamics) covering performance, job execution health, and integration layer telemetry so enterprise customers can observe their ERP stack alongside the rest of their infrastructure. Analyze adoption and customer feedback at scale. Use data from multiple sources to

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for strong backend engineers who love building a developer tools used by the largest AI companies in the world. You’ll be building for things at scale, but also for new AI workflows that change every day. Requirements: Experience building and shipping modern web applications end-to-end. We care more about what you’ve built than how many years you’ve been building. Comfort working across the stack: TypeScript on the frontend, Python services on the backend, and ClickHouse for data and analytics. Deep knowledge of observability tools and patterns used for large-scale workloads such as custom sandboxes, training and inference for large language (LLM) and diffusion models. Experience with at least one of: billing/payments systems, B2B SaaS tooling, or enterprise software, or LLM / diffusion models inference and training loads. Strong product instincts; yo

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 to ship AI products. At Baseten, we are building the global operating system for distributed, heterogeneous AI hardware. We believe that as LLM and multi-modal workloads scale, the network is the computer. We are looking for foundational engineers to lead our GPU Networking efforts, making RDMA a first-class building block in our infrastructure and unlocking the next generation of distributed inference optimizations. THE OPPORTUNITY Networking and compute are no longer separate disciplines; they are converging. The massive throughput of H100, B200, and NVL72 architectures enables and demands a new approach where communication is co-optimized alongside computation. We are entering an era where the network is an active accelerator, leveraging smart hardware offloads and direct interconnects to ensure that data movement operates at wire-speed. In this role, you will go beyond network configuration to architect the software fabric that unifies thousands of GPUs into a cohesive operating system. While you will leverage the best of the open-source ecosystem, you won't be limited by it. Where off-the-shelf solutions stop, you will build from scratch, engineering the primitives required to co-optimize communication and compute for Disaggregated Serving, Wide Expert Parallelism (WideEP), and lightening cold starts. WHAT YOU'LL DO Make RDMA First-Class: You will work on integrating RDMA/RoCE/InfiniBand capabilities directly into our inference stack,

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Senior AI Platform Engineer (DevOps) Who is Mastercard? Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payment choices, making transactions secure, simple, smart, and accessible. Our technology and innovation, partnerships, and networks combined to deliver a unique set of products and services that help people, businesses, and governments realize their greatest potential. Our decency quotient (DQ) drives our culture and everything we do inside and outside our company. We cultivate an environment where individuals can thrive, collaborate, and contribute to innovations that power the global economy. Overview: The AI Platform Engineering team is responsible for building, operating, and evolving Mastercard's enterprise AI platforms and capabilities. Our mission is to provide scalable, secure, and reliable AI infrastructure that enables teams across Mastercard to accelerate the development and deployment of AI-powered solutions. As a Senior AI Engineer, you will help design, implement, and operate the foundational platforms that support AI and machine learning workloads across the enterprise. You will work at the intersect

About the Team OpenAI’s Infrastructure organization builds the systems that power frontier AI workloads at global scale. As compute demand accelerates, our ability to rapidly convert infrastructure investments into usable production capacity has become mission critical. The CPU / Storage / PoP / WAN team is responsible for the end-to-end infrastructure layers required to bring compute online: server and cluster activation, storage platforms, Points of Presence (PoPs), backbone connectivity, and global network expansion. We operate across first-party facilities, colocation environments, and strategic cloud partners to ensure OpenAI can scale reliably and quickly. About the Role We are seeking a highly technical Program Manager to lead execution across CPU, Storage, PoP, and WAN infrastructure programs that directly unlock OpenAI’s next generation compute capacity. In this role, you will own complex cross-functional programs spanning compute cluster activation, storage deployment, PoP bring-up, and backbone expansion. You will coordinate hardware readiness, site readiness, network pathing, storage availability, vendor execution, and engineering dependencies required to turn contracted infrastructure into live training and inference capacity. This role requires strong technical fluency across hardware systems, network infrastructure, storage architecture, and deployment execution. You should be comfortable operating from rack-level implementation details through executive-level capacity planning discussions. This role is based in San Francisco, CA, with travel as needed. Key Responsibilities Lead end-to-end execution of CPU / GPU cluster activation programs across OpenAI’s global infrastructure footprint Drive readiness to convert contracted compute capacity into schedulable production clusters Own deployment programs for new PoPs, backbone nodes, WAN expansion, and interconnection initiatives Build integrated schedules spanning procurement, logistics, installation, st

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 OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role We are looking for an experienced Mechanical Engineer with 7+ years of experience in design of IT hardware from chip/package to system levels. You’ll work alongside experts in thermal, mechanical, electrical, software, and systems engineering to support the design, analysis, and validation of mechanical and thermal systems that ensure the reliability, efficiency, and longevity of mission-critical hardware. This position requires strong analytical skills, hands-on testing experience, and the ability to work in a fast-paced, cross-disciplinary environment. 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 mechanical design for AI supercomputer product in the data center application Collaborate with the cross functional team to design and optimize thermal solutions for data center hardware, including chips, power modules, and system-level cooling architectures Collaborate with cross-functional teams to integrate thermal management strategies into hardware design, from concept to mass production Design and validate mechanical systems, including chassis, enclosures, cooling systems, and high-power connections, ensuring alignment with performance and reliability standards. Perform 3D modeling, FEA, tolerance analysis, and prototyping, ensuring manufacturability and a

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 seeking a Software Engineer to join our First-Party Hardware team. In this role, you will design, build, integrate, and validate the software used to manufacture, qualify, and deliver our hardware from the factory. You will work across the stack to create the infrastructure that runs internally and externally to coordinate all aspects of the production process. You will create the critical tools and procedures to execute, capture, process, and present the data resulting from the end to end assembly and validation of our hardware across multiple vendors and sites. This role is hands-on and high-ownership. You will work closely across teams both internal and external to define the standards that will be used across our products to ensure the velocity and quality of our 1P hardware. You will own the implementation, deployment, and output of these systems as well their continued maintenance and SLAs. Location: San Francisco, CA (Hybrid: 3 days/week onsite). Relocation assistance available. In this role, you will: Design, develop, and maintain the software infrastructure for manufacturing process execution and data export. Own integration across internal customers and vendor systems and processes. Build and maintain the CI, release, and delivery pipeline of tooling to external partners. Build and maintain internal systems to ingest, process, deliver, and visualize critical data for internal teams and systems. Build system health monitoring, telemetry, remote d

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 are seeking a highly skilled Physical Design Engineer with deep expertise in physical design and methodology. This individual contributor role sits within our physical design team and is central to delivering power, performance, and area (PPA) optimized datapath and interconnect solutions for next-generation AI accelerators. You’ll work closely with RTL designers to define and execute on physical design strategies. You will develop tools, flows and methodologies to increase team productivity. Your work will directly impact silicon’s performance and cost efficiency, as well as the team’s execution velocity and quality. In this role, you will: Develop, build and own tools, flows and methodologies for physical implementation Own physical implementation of floorplan blocks from floorplanning to final signoff Collaborate with RTL designers to drive optimal block implementation solutions Analyze and optimize design for timing, power, and area trade-offs, working in collaboration with EDA vendors and ASIC partners Qualifications: BS w/ 4+ or MS with 2+ years or PhD with 0-1 year(s) of relevant industry experience in physical design and methodology development Demonstrated success in taping out complex silicon designs Hands-on experience with block physical implementation and PPA convergence Strong coding experience with python, bazel, TCL Strong experience building physical design tools, flows and methodologies Strong understanding of microarchitecture, RTL design,

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 product manufacturing & quality engineer, who will be responsible for driving technical initiatives related to the manufacturing, quality and reliability of our AI supercomputer hardware systems to ensure product success from concept to launch and through mass production. You’ll have the opportunity to coordinate with functional SMEs and work with a wide range of stakeholders, from design engineering and operations teams, TPMs, external industry vendors and partners to ensure that all products are developed and delivered on time and to the highest quality standards. 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 the integrated manufacturing and quality readiness for a product across L6, L10, and L11, with clear gates, milestones, deliverables, owners, and closure criteria. Lead readiness of process flows, tooling, fixtures, assembly operations, test interfaces, and production controls. Review and contribute to work instructions. Translate product requirements into qualification plans, process controls, test requirements and acceptance criteria with design engineering and Area SMEs Coordinate and drive execution of product and process qualification, reliability testing, and validation with the relevant SMEs. Maintain traceable evidence that assigned products and processes meet agreed performance, reliability,