Compute Country Lead Jobs

RDQ427R198 The Opportunity Multi-cloud is core to Databricks product strategy. Compute serves as the layer that abstracts the cloud from the rest of the company. Building unified infrastructure on top of heterogeneous clouds is a challenge that few companies experience. As an engineer on this team, you won’t just manage infrastructure; you will build it as a product. You will tackle the hard problems of distributed systems: sub-second container/MicroVM startup times, multi-tenant security isolation, and building a unified orchestration layer that scales across AWS, Azure, and GCP. What You’ll Do Design and build the next generation of our Serverless platform, focusing on high availability, low latency, and scale-to-zero efficiency. Build a single compute stack that supports heterogeneous workloads, including GPU instance qualification for AI training and stateful execution for Lakebase. Solve Multi-Cloud Complexity: Develop platform-level abstractions that allow Databricks to run seamlessly across all major cloud providers. Optimize everything from the API gateway down to the host-level networking and container orchestration. Work alongside industry experts who have built world-class systems like Borg, Kubernetes, and Uber’s infrastructure. What We’re Looking For 5+ years of production-level experience in one of: Python, Java, Scala, C++, or a similar language 4+ years of experience developing large-scale distributed systems from scratch Experience with Kubernetes, Docker, or MicroVM technologies (e.g., Firecracker) and a strong grasp of cloud provider internals (AWS/Azure/GCP). You aren't just a user of tools; you understand how to build them from the ground up when existing solutions fail at our scale. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.&n

About Supabase Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. About the Role We are seeking a platform engineer to join our Compute Capacity team. This team owns the capacity plan that keeps compute supply ahead of demand across every region we operate in — the forecasting, buffer policy, and provisioning systems that make sure a project never runs into a wall it didn't know was there. You'll work on the systems that turn a capacity plan into provisioned reality: reservation acquisition, fleet reconciliation, and the automation that keeps what we've committed to in sync with what we're actually running. You'll help build the metrics and alerting that let capacity problems surface months out, on vendor lead time, rather than at the moment someone needs the room. You'll design, build, and operate systems that are both robust and highly automated — helping us hold the right buffer at the right cost, catch drift before it becomes a shortage, and give every team a single, trustworthy view of how much room we have across the millions of databases we manage. What You'll Be Responsible For Help build and maintain the capacity plan that keeps Supabase's compute supply ahead of demand across regions and instance families Support buffer policy by modeling headroom targets and their cost tradeoffs for review and sign-off Build and maintain automation that turns the capacity plan into provisioned reality — reservation acquisition and top-up, fleet reconciliation, drift detection between committed and running capacity Extend our infrastructure as code for capacity-relevant provisioning Instrument capacity: build and maintain metrics for saturation, reservation coverage, idle buffer, forecast error, and provisioning latency Build and tune capacity alerting so headroom,

About the Role We are seeking a Strategic Finance Lead for our GPU compute fleet. In this role, you will be a key partner to our inference and infrastructure teams, providing financial expertise to optimize our compute investments and drive capacity decisions. In this role, you'll develop deep expertise in the economics of AI compute, from token-level serving cost to the long-range financial planning of our GPU fleet. You'll build the models that inform Perplexity's capacity and make-versus-buy decisions, own the internal-cost analysis that underpins internal and external token pricing, and translate complex infrastructure dynamics into clear financial narratives for leadership. This is a high-impact role for someone who thrives at the intersection of finance and infrastructure, and who is energized by building frameworks from scratch in a fast-moving environment. This position is based in San Francisco and requires in-person attendance 2-3 days per week. Key Responsibilities Finance lead for GPU compute spend, including budgeting, monthly forecasting, variance analysis, and financial plan maintenance Build and maintain detailed bottoms-up financial models for the GPU fleet, including capacity forecasts, cost driver analyses, and investment scenario modeling Develop deep expertise in GPU vendor contracts, pricing structures, and cost drivers, and surface optimization opportunities across the fleet Serve as subject matter expert for Perplexity's compute capacity plan, owning source of truth on utilization, committed-versus-consumed spend, and capacity by vendor and cluster Build internal token-cost curves distinguishing marginal from fully loaded serving cost, and translate them into internal and external token pricing Analyze the ROI of in-house inference and training, including opportunity cost across chip types, cluster configurations, and workloads, distilled into a framework for capacity deployment Partner closely with inference and infrastructure engineering to

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

Engineer – Cloud and Compute Platform Teams — 7000 Target Pkwy N,NCD-0375 Brooklyn Park,MN 55445. Apply via Workday.

About the Role As a Strategic Finance Senior Associate at Together, you will own the cost side of our data center build-outs. Reporting to the Director of Strategic Finance, Infrastructure, you will be the financial counterpart to our Infrastructure Strategy team: building and maintaining the cost base for every deployment, validating that build-outs are tracking to plan, and helping evaluate the economics of the sites we take on next. This is a hands-on, high-ownership role at the center of the largest capital decisions the company makes. The ideal candidate has done this before: inside a hyperscaler, neocloud, colocation provider, or data center developer, or covering data centers from the investing side, and pairs real infrastructure fluency with exceptional financial rigor. Responsibilities Own the cost base and cost forecast for Together's data center build-outs, spanning data center non-recurring costs, hardware capex across GPUs, networking, and storage, and ongoing operating costs Validate that build-outs are tracking to plan: maintain budget-versus-actual against approved estimates, flag variances early with a clear read on the driver, and work with Infrastructure Strategy and Infrastructure Engineering to close them out Maintain the all-in unit cost of owned capacity, on a dollars-per-GPU-hour basis by GPU type, as the source of truth used for pricing, margin, and capital allocation decisions Partner with Infrastructure Strategy to evaluate new data center opportunities, building the economics for candidate sites including prepays, financing requirements, tax treatment and incentives, and total cost of ownership over the life of the site Pressure-test hardware cost assumptions and surface savings opportunities with Infrastructure Engineering and Infrastructure Strategy, from equipment choices to storage sizing and cluster configuration trade-offs at different scales Translate hardware delivery timelines and payment milestones maintained by Infrastructure S

About the Team OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. The Infrastructure team is central to this mission, setting the core strategy and implementing the vision. From site selection to deployment to operations, this team sits at the intersection of commercial, technical, and operational domains, interacting with experts and executives inside and outside of OpenAI. We design and operate mission-critical facilities that support cutting-edge AI workloads at scale. About the Role We are seeking a Facilities Operations Lead to support the commissioning, deployment, and long-term operation of our next-generation AI data centers. This role bridges the interface between data center construction and hardware landing, ensuring seamless integration of mission-critical infrastructure with hardware deployment timelines. You will define and execute commissioning plans, support infrastructure bring-up, and take ownership of operations and maintenance for cutting-edge, large-scale, AI data centers. You will collaborate closely with design, construction, and hardware teams to define repeatable processes for new data center builds and lead hands-on operations to uphold the performance and reliability of our deployed infrastructure. Key Responsibilities Define and execute sequences of operations, commissioning steps, and bring-up processes for mission-critical data center facilities. Interface with the design and hardware teams to define deployment procedures tailored to each data center and hardware configuration. Oversee installation, commissioning, and operational readiness of large-scale data center campuses. Manage monitoring, maintenance, and quality control of the data center infrastructure, including high-performance liquid cooling systems. Develop on-site operations staffing strategy. Develop and enforce procedures for planed and unplanned downtime and SLAs for critical

About the Team: Compute Infrastructure builds the platform that turns enormous amounts of compute into a reliable engine for frontier AI. We design, provision, schedule, operate, and optimize the systems that connect accelerators, CPUs, networks, storage, data centers, orchestration software, agent infrastructure, developer tools, and observability into one coherent experience for researchers and product teams. Our work spans the entire stack: capacity planning and cluster lifecycle, bare-metal automation, distributed systems, Kubernetes and scheduling, deep system optimization, high-performance networking, storage, fleet health, reliability, workload profiling, benchmarking, and the developer experience that lets teams use enormous compute systems with confidence. At this scale, small improvements to communication, scheduling, hardware efficiency, or debugging workflows can compound into meaningful research velocity. We are hiring across Compute Infrastructure rather than for a single narrow team, and we use this opening to match strong engineers to the problems where they can have the most leverage. About the Role We are looking for engineers who want to build the compute platform behind OpenAI's research and products. You may not be the strongest in low-level systems, high-performance computing, distributed infrastructure, reliability, CaaS, agent infrastructure, developer platforms, tooling, or the user experience around infrastructure. What matters is that you can reason carefully about complex systems, write durable software, and raise the quality and velocity of the people around you. Depending on your background and interests, you might work close to hardware, close to users, on CaaS and agent infrastructure, or on the control planes and data planes in between. You could help bring new supercomputing capacity online, optimize training workloads from profiler traces and benchmarks, improve NCCL and collective communication behavior, reason about GPUs, NICs, t

Zoox has embarked on a highly ambitious journey to develop a full-stack autonomous mobility solution for our cities. We’re looking for a technical program manager to drive cross-functional programs delivering our next-generation compute platform and sensor architecture — the hardware and software backbone of our autonomous vehicle stack. You'll own program strategy, execution, and risk management across hardware, embedded software, and systems integration teams, working closely with hardware engineering, perception, and platform software groups to ship on schedule. In this role, you will: Own the end-to-end program plan for next-gen compute and sensor software workstreams, from architecture definition through bring-up, validation, and production readiness. Partner with hardware, firmware, perception, and systems engineering leads to align on requirements, interfaces, and milestones across the compute/sensor stack. Identify and drive resolution of cross-team dependencies, technical risks, and schedule conflicts before they become blockers. Build and maintain program schedules, tracking mechanisms, and executive-level status reporting. Facilitate technical trade-off discussions (performance, power, cost, timeline) and drive decisions to closure with engineering leadership. Establish and evolve program management processes (planning cadences, milestone reviews, launch readiness criteria) for a fast-moving hardware-software program. Qualifications BS or MS degree in computer science, engineering or equivalent job experience 8+ years of technical program management experience, with a track record on programs spanning embedded software and hardware (compute platforms, SoCs, sensors, or similar) Strong track record of managing complex, long-running, cross-functional projects Deep familiarity with software, hardware, or automotive development processes An ability to keep the big

About the Team Industrial Compute is building the infrastructure ecosystem that enables OpenAI to train and deploy increasingly capable AI systems at unprecedented scale. The organization operates across compute supply, demand, infrastructure, partnerships, and the physical and commercial systems required to make large-scale compute available. Industrial Compute Strategy & Operations serves as the connective operating layer across this ecosystem. The team works directly with senior leadership across Scaling, Finance, Partnerships, Research, and Infrastructure to translate ambiguous, high-impact challenges into clear strategies, scalable operating mechanisms, and decisive execution. This team is responsible for ensuring that OpenAI’s compute strategy evolves into durable competitive advantage by identifying systemic constraints, aligning stakeholders around critical decisions, and driving the operating mechanisms required to execute at scale. About the Role We are seeking a highly experienced Strategic Operations leader to help shape and operationalize OpenAI’s compute strategy across supply, demand, infrastructure, partnerships, and commercial strategy. This is a senior individual contributor role operating at the intersection of strategy, operations, infrastructure, and executive decision-making. You will work closely with compute leadership to identify the most consequential problems facing the organization, develop structured approaches to solving them, align stakeholders across the company, and drive initiatives from ambiguous concepts through execution. The role will span both strategic and operational work. You may develop long-range compute strategies and investment frameworks, evaluate build-versus-buy decisions, shape major commercial transactions, establish organizational planning mechanisms, or take ownership of a cross-functional initiative that does not have a clear organizational home. Success in this role requires exceptional judgment, analytical

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui

Senior Software Engineer - Analytics Compute Platform Team About the Role & Team Every chart, insight, and experiment result a customer sees in Amplitude passes through the compute layer that this team owns. Our team sits between Amplitude's front-end analytics products/ rest APIs/ MCPs and Nova, our proprietary analytics database, and owns the compute API that translates a user's question into a fast, correct answer. Our mandate: enable a highly performant, reliable, and flexible way to compute insights. Those three goals are often in tension the more flexible we make the system, the harder it is to keep it fast and simple, and a lot of the interesting engineering work on this team lives in that tradeoff. Day to day, you'll work closely with engineers on data management, marketing analytics, Session Replay, Experiment, CDP, Query, and various product teams, since they're all consumers of what we build. As a Senior Software Engineer, you will Design and build core parts of the query/compute engine that powers analysis across Amplitude's product suite Evolve the compute API and semantic layer that other engineering teams build features on top of, so that it can support a more generic table Help unify and evolve our core data model, including how non-event data (profile properties, lookup tables, etc.) is represented alongside event data Improve the performance, reliability, and scalability of query planning and execution on the Amplitude query engine Partner with teams across Session Replay, Experiment, CDP, Query, and frontend to understand their needs and shape the compute layer around them Take ownership of projects end-to-end, from design through rollout You'll be a great addition to the team if you have Strong backend or distributed-systems engineering experience, ideally touching OLAP databases, query engines, or data infrastructure Experience with SQL, query planning/execution, or building APIs that many other engineering teams depend on Comfort reasoning

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. We are seeking a visionary Principal Software Engineer to join our Compute organization and provide technical leadership for our Kubernetes infrastructure. You will drive the evolution of a platform that powers our global scale operations, transforming Kubernetes into a secure, reliable, and invisible foundation for our developers across our on-prem and public cloud fleet. Your mission is to balance cutting-edge innovation with rigorous platform stability, ensuring that internal and external customers have a seamless, high-performance experience at massive scale. You Will: Architectural Leadership: Serve as a technical lead for our Kubernetes ecosystem, setting the long-term architectural strategy for a platform that manages thousands of nodes and supports millions of concurrent requests. Customer Focus: Think deeply about how our internal customers consume and interact with compute, designing intuitive interfaces and tooling that simplify consumption of complex infrastructure services. Deep-Dive Engineering: Leverage deep expertise in Kubernetes internals, including custom controllers, operators, API server architecture, and etcd, to solve complex scaling bottlenecks and optimize our contr

Senior: PLN 260,400 - 352,200 Staff: PLN 350,700 - 474,400 Subject to alignment to the responsibilities and duties of the role - we currently have multiple positions available at both Senior and Staff level. Location: Gdańsk. This role is not available as fully remote. About the job Build the AI compute libraries that turn next-generation hardware into real performance. As a Staff Software Engineer, you will design and optimise high-performance compute kernels for AI workloads. You will work across linear algebra, tensor operations, numerical correctness and low-level performance. Your work will help customers get more from advanced AI hardware. That means shaping the libraries behind faster, more reliable AI systems at scale. You will write C++ and Python, profile on Linux and make hard trade-offs across memory, threading and numerical behaviour. You will also guide technical direction, review designs and help engineers make better decisions. This role suits someone who wants deep technical ownership without moving away from hands-on engineering. The team and culture You will join the ML Kernels & Runtime team, which builds the compute libraries that expose hardware performance to customers. The work is technical, detailed and close to the machine. Engineers own problems from design through validation, benchmarking and production quality. Decisions are made through evidence, clear technical reasoning and open debate. You will move quickly, speak up when something can be better and help others raise the quality of their work. Leadership here means taking responsibility for outcomes, not waiting for permission. What we’re looking for Excellent C++ and Python skills, with experience building performance-sensitive software Strong understanding of processor architectures, Linux profiling and low-level optimisation Proven technical leadership, including guiding engineering direction, reviewing designs and mentoring others Ability to balance hands-on implem