We're seeking a highly skilled Member of Technical Staff to join our Compute Infrastructure team. As a key member of this team, you will design, build, and operate massive-scale clusters and orchestration platforms that power frontier AI training, inference, and agent workloads at unprecedented scale.
\nIn this role, you will push the boundaries of container orchestration far beyond existing systems like Kubernetes, manage exascale compute resources, optimize for high-performance training runs and production serving, and collaborate closely with research and systems teams to deliver reliable, ultra-scalable infrastructure that enables xAI's next-generation models and applications.
\nResponsibilities include building and managing massive-scale clusters, designing, developing, and extending an in-house container orchestration platform, collaborating with research teams to architect and optimize compute clusters, profiling, debugging, and resolving complex system-level performance bottlenecks, and owning end-to-end infrastructure initiatives.
\nTo succeed in this role, you will need deep expertise in virtualization technologies and advanced containerization/sandboxing, strong proficiency in systems programming languages such as C/C++ and Rust, and proven track record profiling, debugging, and optimizing complex system-level performance issues.
\nPreferred skills and experience include experience in Linux kernel development, hypervisor extensions, or low-level system programming for compute-intensive workloads, operating or designing large-scale AI training/inference clusters, and familiarity with performance tools, tracing, and debugging in production distributed environments.
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\nYour expertise in low-level system programming, kernel optimization, and virtualization technologies will be crucial in ensuring Anthropic can scale our compute infrastructure efficiently and reliably for training and serving frontier AI models.
\nResponsibilities:
\nOptimize our virtualization stack, improving performance, reliability, and efficiency of our VM environments
\nDesign and implement kernel modules, drivers, and system-level components to enhance our compute infrastructure
\nInvestigate and resolve performance bottlenecks in virtualized environments
\nCollaborate with cloud engineering teams to optimize interactions between our workloads and underlying hardware
\nDevelop tooling for monitoring and improving virtualization performance
\nWork with our ML engineers to understand their computational needs and optimize our systems accordingly
\nContribute to the design and implementation of our next-generation compute infrastructure
\nShare knowledge with team members on low-level systems programming and Linux kernel internals
\nPartner with cloud providers to influence hardware and platform features for AI workloads
\nYou may be a good fit if you:
\nHave experience with Linux kernel development, system programming, or related low-level software engineering
\nUnderstand virtualization technologies (KVM, Xen, QEMU, etc.) and their performance characteristics
\nHave experience optimizing system performance for compute-intensive workloads
\nAre familiar with modern CPU architectures and memory systems
\nHave strong C/C++ programming skills and ideally experience with systems languages like Rust
\nUnderstand Linux resource management, scheduling, and memory management
\nHave experience profiling and debugging system-level performance issues
\nAre comfortable diving into unfamiliar codebases and technical domains
\nAre results-oriented, with a bias towards practical solutions and measurable impact
\nCare about the societal impacts of AI and are passionate about building safe, reliable systems
\nStrong candidates may also have experience with:
\nGPU virtualization and acceleration technologies
\nCloud infrastructure at scale (AWS, GCP)
\nContainer technologies and their underlying implementation (Docker, containerd, runc, OCI)
\neBPF programming and kernel tracing tools
\nOS-level security hardening and isolation techniques
\nDeveloping custom scheduling algorithms for specialized workloads
\nPerformance optimization for ML/AI specific workloads
\nNetwork stack optimization and high-performance networking
\nExperience with TPUs, custom ASICs, or other ML accelerators
\nRepresentative projects:
\nOptimizing kernel parameters and VM configurations to reduce inference latency for large language models
\nImplementing custom memory management schemes for large-scale distributed training
\nDeveloping specialized I/O schedulers to prioritize ML workloads
\nCreating lightweight virtualization solutions tailored for AI inference
\nBuilding monitoring and instrumentation tools to identify system-level bottlenecks
\nEnhancing communication between VMs for distributed training workloads
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\nResponsibilities:
\nBasic Qualifications:
\nPreferred Skills and Experience:
\nCompensation and Benefits:
\n$180,000 - $440,000 USD
\nBase salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.
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\nThe MLS team at Freenome develops DL models using massive-scale genomic data that presents significant challenges for current training paradigms. The Senior Machine Learning Research Engineer will primarily be responsible for developing and deploying the infrastructure needed to support development of such DL models: enabling distributed DL pipelines, optimising hardware utilisation for efficient training, and performing model optimisations.
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\nNice-to-haves include:
\nThe US target range of our base salary for new hires is $161,925 - $227,325. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.
\nFreenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, colour, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.
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\nAnthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
\nResponsibilities:
\nWe are seeking a Linux OS and System Programming Subject Matter Expert to join our Infrastructure team. In this role, you'll work on accelerating and optimising our virtualisation and VM workloads that power our AI infrastructure. Your expertise in low-level system programming, kernel optimisation, and virtualisation technologies will be crucial in ensuring Anthropic can scale our compute infrastructure efficiently and reliably for training and serving frontier AI models.
\nYou may be a good fit if you:
\nStrong candidates may also have experience with:
\nRepresentative projects:
\nDeadline to apply:
\nNone. Applications will be reviewed on a rolling basis.
\nLogistics
\nEducation requirements:
\nWe require at least a Bachelor's degree in a related field or equivalent experience.
\nLocation-based hybrid policy:
\nCurrently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
\nVisa sponsorship:
\nWe do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
\nWe encourage you to apply even if you do not believe you meet every single qualification.
\nNot all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.
\nYour safety matters to us.
\nTo protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about the authenticity of an email or a request, please reach out to us directly.
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\nPioneering the next generation of AI requires breakthrough innovations in GPU performance and systems engineering. As a GPU Performance Engineer, you'll architect and implement the foundational systems that power Claude and push the frontiers of what's possible with large language models. You'll be responsible for maximizing GPU utilization and performance at unprecedented scale, developing cutting-edge optimizations that directly enable new model capabilities and dramatically improve inference efficiency.
\nWorking at the intersection of hardware and software, you'll implement state-of-the-art techniques from custom kernel development to distributed system architectures. Your work will span the entire stack—from low-level tensor core optimizations to orchestrating thousands of GPUs in perfect synchronization.
\nStrong candidates will have a track record of delivering transformative GPU performance improvements in production ML systems and will be excited to shape the future of AI infrastructure alongside world-class researchers and engineers.
\nYou might be a good fit if you:
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\nRepresentative projects:
\nDeadline to apply: None. Applications will be reviewed on a rolling basis.
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\nLinux Kernels Software Lead
\nLocation
\nSan Francisco
\nEmployment Type
\nFull time
\nDepartment
\nScaling
\nCompensation
\nThe base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.
\nMore details about our benefits are available to candidates during the hiring process.
\nThis role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.
\nAbout the Team
\nThe Scaling team builds and optimizes large-scale infrastructure to enable next-generation AI workloads.
\nAbout the Role
\nWe’re looking for a founding/lead Linux kernel developer to join our Scaling team. In this role, you’ll design and develop Linux kernel components, working at the intersection of hardware and software to unlock performance at scale.
\nResponsibilities
\nQualifications
\n_To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements as provided in those laws and regulations._
\nAbout OpenAI
\nOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
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\nLocation
\nSan Francisco
\nEmployment Type
\nFull time
\nLocation Type
\nHybrid
\nDepartment
\nConsumer Products
\nCompensation
\nThe base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.
\nBenefits
\nAbout the Team
\nThe Software Engineering Embedded team builds reliable, high-performance systems on custom hardware. We work closely with hardware engineers to design, optimize, and ship software that bridges cutting-edge devices and real-world constraints like memory, power, and latency. Our work spans early prototyping through product launch, ensuring that our embedded platforms are robust, efficient, and production-ready.
\nAbout the Role
\nAs an Embedded Software Engineer, you will design, implement, and debug software for embedded devices. You’ll own low-level bring-up, write production C/C++ code, and partner closely with hardware teams to deliver reliable, high-performance systems.
\nWe’re looking for engineers with deep embedded expertise, strong debugging skills, and a passion for building systems that perform under real-world conditions.
\nThis role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees.
\nIn this role, you will:
\nYou might thrive in this role if you:
\nAbout OpenAI
\nOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
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\nMicrosoft are looking for a talented Principal Software Engineer at their Beijing office. This role sits at the heart of AI infrastructure development, driving innovation in large-scale AI infrastructure. You will be instrumental in designing and implementing high-performance, massively scalable infrastructure required to deploy frontier LLM models.
\nAbout the Role
\nAs a Principal Software Engineer on the AI Infrastructure team, you will be responsible for designing and implementing innovative system optimization solutions for internal LLM workloads. You will optimize LLM inference workloads through innovative kernel, algorithm, scheduling, and parallelization technologies. You will also continuously develop and maintain internal LLM inference infrastructure, discovering new LLM system optimization needs and innovations.
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\nAbout the Role
\nWe are seeking brilliant and passionate engineers to work with us on the most interesting and challenging problems of AI Infrastructure development. As a Senior Software Engineer, you will be responsible for designing and implementing the high-performance, massively scalable infrastructure required to deploy frontier LLM models through innovative GPU kernel, compression, scheduling and parallelization optimizations.
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\nWhat you need
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