Compute Country Lead Jobs

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. Compute is our newly launched microVM architecture for running agentic workloads, operating alongside our existing Edge Functions service for server-side TypeScript functions distributed globally at the edge. We want developers to be able to build truly global applications by distributing both compute and data globally. Infrastructure concerns like regions, cold starts, CPU and memory provisioning should fade into the background so developers can focus on iterating on business logic, and fast, flexible runtimes a growing range of agent-driven code. We are looking for experienced and passionate engineers to help us go further in this vision. What You’ll Own Help build & architect the Supabase Compute platform, built on Firecracker microVMs. Implementing monitoring, alerting, and OpenTelemetry tracing across the runtime, then using that visibility to drive optimizations that improve latency and reliability of the service. Working closely with the Firecracker, Deno, and other open-source teams, contributing to upstream and relaying our users' requirements. Participating in an on-call rotation to keep Compute healthy in production. Help manage and improve features like scheduled functions, background tasks, WebSockets streaming, ephemeral file storage, and custom routing. Integrating Compute more tightly with the rest of the Supabase stack — Auth, Postgres, Storage, and Realtime. Expanding the Compute runtime to support more use cases (AI inference, MCP servers, hosting simple websites, URL shorteners). Improving the DX of developing and debugging Compute locally through the Supabase CLI, including DevTools integration, logging, and production parity. What You’ll Bring At least 5 years of backe

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of a best-in-class family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from a diverse group of backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a senior validation lead engineer to lead at-scale rack validation efforts for next-generation AI hyperscale systems. This role focuses on post-silicon system validation across the full lifecycle, ensuring functional, electrical, and thermal performance meets product objectives. You will own end-to-end blade and rack validation including planning, development, execution, and debug while collaborating across firmware, systems, and hardware teams. The Team The 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. Responsibilities and Duties Lead post-silicon validation of AI compute blades and racks including test planning, development, and automation. Drive provisioning and integration of system components (SoC FW, BMC, RMC, OS) for rack-level readiness. Own execution against program achievements and report validation progress and risks. Triage test failures, collect debug data, and collaborate on root cause analysis. Track

About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you’ll heighten your potential and broaden your horizons - all while shaping the future of connectivity. Role Summary We are looking for a highly driven Hardware Engineer who is passionate about innovation and eager to build extraordinary products. In this role, you will help design next-generation Storage Server solutions, including high-density NAS, SAN, and unified storage systems with real global impact. You will collaborate directly with R&D labs across multiple countries, bringing your expertise, energy, and creativity into every stage of development. We value engineers who think beyond conventional solutions, embrace new challenges, and consistently engineer reliable, high-performance enterprise storage products. Responsibilities Collaborate with a global cross-functional team—including industrial design, layout, mechanical, SI, BSP, thermal, DQA, and product management—to drive new product development from concept through mass production. Lead or contribute to system architecture for storage servers, owning schematic capture, component selection, and PCB layout review to ensure ultra-high-speed signal integrity and robust high-power design. Design and validate high-density storage backplanes and connectivity solutions (e.g., NVMe/SATA/SAS topologies). Rapidly prototype concept hardware for mock-ups and feasibility studies; take a hands-on role in board bring-up, debugging, testing, and validation.

About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you’ll heighten your potential and broaden your horizons - all while shaping the future of connectivity. About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to the next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you’ll heighten your potential and broaden your horizons, all while shaping the future of connectivity. Role Summary We are looking for a highly driven Hardware Engineer who is passionate about innovation and eager to build extraordinary products. In this role, you will help design next-generation Storage Server solutions, including high-density NAS, SAN, and unified storage systems with real global impact. You will collaborate directly with R&D labs across multiple countries, bringing your expertise, energy, and creativity into every stage of development. We value engineers who think beyond conventional solutions, embrace new challenges, and consistently engineer reliable, high-performance enterprise storage products. Responsibilities Collaborate with a global cross-functional team—inc

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

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking an Interconnect and Compute Architect to help define and build next-generation CPU networking architecture for both datacenter and emerging robotics/automotive applications. You will contribute to our current datacenter networking efforts while also helping to seed and specify future medium- to low-power robotics/automotive devices for AI/ML compute and sensor ingest. The initial focus will be datacenter networking, with robotics as the first target within the automotive/robotics space. This role is remote, based out of North America. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are You thrive while navigating multiple priorities and ambiguous, evolving requirements. You have knowledge of Ethernet network architecture and how performance is modeled. You have experience with die-to-die interfaces and understand associated protocols and design tradeoffs. You understand Ethernet networking concepts and how they map onto on-chip and off-chip fabrics You have experience with datacenter scale up architectures like UALink, NVLink, and Broadcom SUE. You have experience with scale out RDMA protocols like RoCE, Infinib

About the Role Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the [Together GPU Clusters](https://www.together.ai/gpu-clusters) flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Senior Software Engineer focusing on AI Compute in the Together Cloud org, you will build and own major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware: GB300s/VRs, BlueField DPUs, InfiniBand and dual/quad-plane RoCEv2 fabrics. That virtualized computing platform powers our own SaaS products – inference, RL, and fine-tuning – and serves external cloud customers through self-serve offerings such as on-demand/reserved Kubernetes/Slurm clusters, across dozens of data centers and hundreds of thousands of GPUs. The hard problems in rapidly scaling heterogeneous GPU fleets are software problems: fully automated bootstrapping of GPU data centers, high-performance virtualization of GPU compute and DC networking without compromising isolation or portability, and fault-tolerant decentralized control planes. We solve them by building global and in-DC services, Kubernetes operators, and high-performance SDN libraries, forking hypervisors and Linux kernels, and building infra tailored to inference and fine-tuning. You'll own massive greenfield projects across their full lifecycle – scoping the problem and writing PRDs with our PMs, designing the system, and building it through to GA launch. Responsibilities Build the GPU and network virtualization stack: the hypervisor, kernel, and SDN work that makes GPU compute and DC networking high-perform

About the Role Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the [Together GPU Clusters](https://www.together.ai/gpu-clusters) flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Senior Software Engineer focusing on AI Compute in the Together Cloud org, you will build and own major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware: GB300s/VRs, BlueField DPUs, InfiniBand and dual/quad-plane RoCEv2 fabrics. That virtualized computing platform powers our own SaaS products – inference, RL, and fine-tuning – and serves external cloud customers through self-serve offerings such as on-demand/reserved Kubernetes/Slurm clusters, across dozens of data centers and hundreds of thousands of GPUs. The hard problems in rapidly scaling heterogeneous GPU fleets are software problems: fully automated bootstrapping of GPU data centers, high-performance virtualization of GPU compute and DC networking without compromising isolation or portability, and fault-tolerant decentralized control planes. We solve them by building global and in-DC services, Kubernetes operators, and high-performance SDN libraries, forking hypervisors and Linux kernels, and building infra tailored to inference and fine-tuning. You'll own massive greenfield projects across their full lifecycle – scoping the problem and writing PRDs with our PMs, designing the system, and building it through to GA launch. Responsibilities Build the GPU and network virtualization stack: the hypervisor, kernel, and SDN work that makes GPU compute and DC networking high-perform

P-931 At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. At Databricks, the Compute Infrastructure organization builds and operates the foundation that runs all Data, AI and stateful workloads across all major clouds. Our platform launches tens of millions of VMs per day, operates thousands of Kubernetes clusters, and must deliver extreme elasticity, reliability and cost efficiency. We are looking for an Engineering Manager to lead a team responsible for critical components of this platform. Your work will directly influence product velocity, customer experience, and the company’s ability to scale. The impact you will have: Own and evolve the compute platform to support all Databricks workloads , enabling engineers to build world-class products with high velocity and best-in-class performance. Hire exceptional engineers and invest in their growth through coaching, feedback, and career development. Raise the technical and operational bar through strong design practices, testing, and a culture of engineering excellence and platform mindset . Partner with engineering and product leadership to define long-term strategy and roadmaps. Lead cross-team initiatives that span product and infrastructure surface areas. Influence architectural decisions beyond your immediate team. What we look for: 10+ years of experience building and operating large-scale distributed systems , including strong prac

Zoox made the world’s first purpose-built commercial robotaxi, combining advanced self-driving hardware and software. In order to ensure safe operation, low latency and consistent resource utilization are critical. The Planner Compute team is responsible for the performance of the largest single software component within the autonomy stack, the motion planner. The Planner Compute team is looking for an expert in GPU performance. You will instrument, monitor, analyze and optimize GPU-based algorithms that are performance-critical for our solution. The scope for GPU usage ranges from machine learning inference to custom CUDA kernels written specifically for the motion planner. In this role, you will: Analyze performance metrics to identify GPU hotspots and optimizations Contribute to the adaptation of our current planner to multiple GPU architectures with different resources Optimize ML models for latency and GPU memory usage Support engineers within Planner as a subject matter expert on CUDA & GPU performance Qualifications BS in computer science or related field and 8+ years of experience. Strong knowledge of CUDA as applied to recent GPU microarchitectures (e.g., Ampere, Blackwell) and experience debugging/optimizing GPU kernels using tools like Nsight. Strong knowledge of C++ and experience in large code bases, comfortable in Linux development environments. Experience in development, debugging, and profiling of complex multiprocess systems (e.g., robotic systems, game engines). Bonus Qualifications GPU kernel development experience There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies onl

Zoox’s Advanced Hardware Engineering team is in charge of delivering all the autonomous hardware, infotainment electronic control units and electrical components that go into Zoox’s future fleet of self-driving vehicles. At the heart of our hardware architecture is the Primary Compute Unit (PCU) - the compute system that runs the AI stack that enables the vehicle to drive autonomously. We are looking for a seasoned technical program manager own the PCU program end-to-end, including the integrated program schedule. In this role, you will work cross-functionally with our vehicle engineering, systems engineering, software, safety, supply chain, quality, manufacturing and integration teams to achieve our strategic objectives and tactical milestones. You will develop project schedules with numerous dependencies, map program milestones to company milestones, flag and mitigate risks, estimate and maintain budgets, identify solutions to complex problems, navigate ambiguity, all the while holding teams accountable and clearly communicating expectations and ongoing progress. As with any startup, we move fast here at Zoox, and many candidates will be asked from time to time to wear many hats. We would love to hear from you if you are up for solving very challenging problems across numerous cross-functional teams, delivering milestones with numerous dependencies, and scaling your impact by developing and adopting structured ways of working. Additionally, if you are an expert at herding cats and influencing without formal authority, then this role was made for you! In this role, you will: Drive the PCU program forward with thought and energetic leadership, including supporting architecture alignment, hardware development, validation, integration, cross-functional alignment and company-wide communication. This will be done in close partnership with the technical lead and other core team members across multiple departments. Work with department le

As a Staff Engineer on Datadog's Compute – Disruption and Workload Placement team, you'll help define how our Kubernetes fleet scales to meet the demands of rapidly growing AI and cloud-native workloads. You'll work on the systems that ensure engineering teams have the right compute capacity, in the right region, at the right time across AWS, Google Cloud, and Azure. This is a highly technical, high-impact role where you'll shape the future of capacity orchestration, influence platform architecture, and solve infrastructure challenges that directly support Datadog's continued growth. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Lead the technical direction of capacity management and workload placement for Datadog's Kubernetes platform spanning 100,000+ virtual machines across multiple cloud providers. Design and build systems that optimize how engineering workloads are scheduled and deployed across regions while balancing capacity constraints, reliability, and performance. Partner across infrastructure teams to evolve multi-region and multi-cloud capacity orchestration as Datadog continues to scale. Develop production software in Go to improve Kubernetes platform capabilities, automation, and operational efficiency. Use data and capacity signals to influence infrastructure decisions, forecast growth, and improve workload placement strategies. Who You Are: You have significant experience designing and operating large-scale Kubernetes-based infrastructure or platform systems. You are an experienced software engineer with strong programming skills, ideally in Go or a comparable systems programming language. You have hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure) and understand distributed cloud infrastructure. Yo

As a Staff Engineer on Datadog's Compute – Disruption and Workload Placement team, you'll help define how our Kubernetes fleet scales to meet the demands of rapidly growing AI and cloud-native workloads. You'll work on the systems that ensure engineering teams have the right compute capacity, in the right region, at the right time across AWS, Google Cloud, and Azure. This is a highly technical, high-impact role where you'll shape the future of capacity orchestration, influence platform architecture, and solve infrastructure challenges that directly support Datadog's continued growth. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Lead the technical direction of capacity management and workload placement for Datadog's Kubernetes platform spanning 100,000+ virtual machines across multiple cloud providers. Design and build systems that optimize how engineering workloads are scheduled and deployed across regions while balancing capacity constraints, reliability, and performance. Partner across infrastructure teams to evolve multi-region and multi-cloud capacity orchestration as Datadog continues to scale. Develop production software in Go to improve Kubernetes platform capabilities, automation, and operational efficiency. Use data and capacity signals to influence infrastructure decisions, forecast growth, and improve workload placement strategies. Who You Are: You have significant experience designing and operating large-scale Kubernetes-based infrastructure or platform systems. You are an experienced software engineer with strong programming skills, ideally in Go or a comparable systems programming language. You have hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure) and understand distributed cloud infrastructure. Yo

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Through strategic partnerships and self-built campuses, we are scaling one of the world's fastest-growing AI infrastructure platforms. The Supply Chain organization ensures critical infrastructure components—from compute systems and networking equipment to integrated rack solutions—are sourced, manufactured, qualified, and delivered with the speed and reliability required to support frontier AI development. We partner closely with Hardware Engineering, Manufacturing Quality Engineering, Infrastructure Delivery, Hardware Operations, Finance, and suppliers worldwide to build a resilient, scalable supply chain capable of supporting rapid infrastructure expansion. As Industrial Compute continues to grow, Supply Chain serves as the operational bridge between engineering innovation and large-scale infrastructure deployment. About the Role We are seeking a Supply Chain Manager to lead strategic execution across sourcing, supplier operations, manufacturing quality, and infrastructure delivery for OpenAI's AI infrastructure portfolio. This role will oversee a multidisciplinary team responsible for strategic sourcing, manufacturing quality engineering, and technical program management while partnering closely with engineering, finance, hardware operations, and deployment teams. You will drive supplier strategy, manufacturing readiness, production planning, quality performance, and operational execution across the full hardware lifecycle. Success requires balancing long-term supplier strategy with day-to-day execution. You'll establish scalable operating mechanisms, strengthen supplier partnerships, manage complex cross-functional programs, and ensure OpenAI can rapidly deploy AI infrastructure without compromising quality, cost, or reliability. This is a people leadership role responsible for developing a high-performing organization while driving operati

About the Team OpenAI’s Compute Strategy team is responsible for securing and scaling the core resources that power our research and products. We partner across engineering, finance, legal, and operations to identify, negotiate, and execute strategic partnerships that expand OpenAI’s capacity for compute, power, and data center infrastructure. Our mandate spans energy procurement, real estate development, colocation, cloud service providers, silicon and strategic supply chain, and infrastructure financing—ensuring OpenAI can grow with speed, resilience, and cost-efficiency. About the Role We are hiring several Business Development Lead, Compute Strategy positions focused on compute infrastructure. Each hire will bring deep expertise in one or more focus areas while collaborating across the broader infrastructure stack. In this role, you will source opportunities, structure partnerships, and negotiate high-value agreements across OpenAI’s infrastructure ecosystem. You will work directly with external partners and suppliers while collaborating internally with engineering, legal, finance, and operations to ensure we have the resources needed to support state-of-the-art AI systems. This role requires technical fluency, commercial judgment, and disciplined execution. Your work will directly shape how quickly, reliably, and efficiently OpenAI can bring new compute capacity online. Each hire will focus on building partnerships and executing deals in one or more of the following areas: Energy and Power: securing scalable and sustainable energy supply. Land and Real Estate: identifying and securing strategic sites. Colocation : evaluating and contracting for third-party data center capacity. Cloud Service Providers (CSPs): structuring partnerships with hyperscalers and specialized AI cloud providers. Silicon: building semiconductor partnerships to secure advanced silicon and resilient long-term supply. Fiber & Equipment: securing fiber & critical data center equipmen