Linux Kernels Software Lead

About Our Team At OpenAI, our Scaling team is dedicated to developing and fine-tuning large-scale infrastructure that empowers the next generation of AI workloads. We are passionate about pushing the limits of technology to create impactful AI systems that benefit everyone.Role Overview We are seeking a pioneering Lead Linux Kernel Developer to join our Scaling team. In this pivotal role, you will architect and implement Linux kernel components, bridging the gap between hardware and software to enhance performance and scalability for our advanced AI initiatives.Key ResponsibilitiesSpearhead the development of our Linux kernel stack tailored for high-performance systems.Design and create kernel drivers, focusing on areas such as DMA, PCIe, NICs, and RDMA.Oversee the full development cycle of system-scale networking, including essential kernel and low-level software components.Collaborate with technology vendors to effectively integrate their solutions into our systems.Conduct kernel bring-up and debugging on new hardware platforms.Develop userspace software to facilitate integration, testing, diagnostics, and performance validation.Required QualificationsDemonstrated experience in leading Linux kernel development projects.In-depth knowledge of key subsystems for high-performance systems such as PCIe, dma-buf, RDMA, P2P, SR-IOV, and IOMMU.Familiarity with subsystems and frameworks relevant to scalable networking, including ibverbs and ECN/DCQCN.Expertise in programming languages such as C, C++, Python, and Linux shell scripting; experience with Rust is highly desirable.Proven ability to collaborate with engineering teams to define interfaces and develop tooling.Successful history of managing vendor relationships and deliverables.Background in embedded systems development, including bootloaders, drivers, and hardware/software integration.Ability to navigate ambiguity and construct systems from the ground up.Note: To comply with U.S. export control laws, candidates for this position may need to meet specific legal status requirements.

P-1285 About This Role Join our dynamic team at Databricks as a Staff Software Engineer specializing in GenAI Performance and Kernel. In this pivotal role, you will take charge of designing, implementing, and optimizing high-performance GPU kernels that drive our GenAI inference stack. Your expertise will lead the development of finely-tuned, low-level compute paths, balancing hardware efficiency with versatility, while mentoring fellow engineers in the intricacies of kernel-level performance engineering. Collaborating closely with machine learning researchers, systems engineers, and product teams, you will elevate the forefront of inference performance at scale. What You Will Do Lead the design, implementation, benchmarking, and maintenance of essential compute kernels (such as attention, MLP, softmax, layernorm, memory management) tailored for diverse hardware backends (GPU, accelerators). Steer the performance roadmap for kernel-level enhancements, focusing on areas like vectorization, tensorization, tiling, fusion, mixed precision, sparsity, quantization, memory reuse, scheduling, and auto-tuning. Integrate kernel optimizations seamlessly with higher-level machine learning systems. Develop and uphold profiling, instrumentation, and verification tools to identify correctness, performance regressions, numerical discrepancies, and hardware utilization inefficiencies. Conduct performance investigations and root-cause analyses to address inference bottlenecks, such as memory bandwidth, cache contention, kernel launch overhead, and tensor fragmentation. Create coding patterns, abstractions, and frameworks to modularize kernels for reuse, cross-backend compatibility, and maintainability. Influence architectural decisions to enhance kernel efficiency (including memory layout, dataflow scheduling, and kernel fusion boundaries). Guide and mentor fellow engineers focused on lower-level performance, conducting code reviews and establishing best practices. Collaborate with infrastructure, tooling, and machine learning teams to implement kernel-level optimizations in production and assess their impacts.

About the Role OpenAI is looking for a Software Engineer specializing in Kernel Performance and AI Tooling to join the team in San Francisco. This role centers on improving software systems for maximum efficiency and building advanced tools that support AI development. What You Will Do Optimize kernel-level performance across OpenAI's software stack. Design and implement tools that accelerate AI research and deployment. Work closely with engineers to identify bottlenecks and deliver practical solutions. Contribute to technical discussions and share knowledge with teammates. Team and Collaboration Work alongside engineers who are committed to advancing AI technology. Collaboration and innovation are central to the team’s approach.

Be Part of a Team Transforming Autonomy in ConstructionAt Bedrock Robotics, we are revolutionizing the application of AI beyond research by implementing it in real-world scenarios. Our team consists of seasoned professionals who played pivotal roles in launching Waymo, scaling Segment to a $3.2 billion acquisition, and driving Uber Freight to $5 billion in revenue. We are currently deploying autonomous systems in heavy construction machinery nationwide, enhancing the efficiency of multi-billion dollar infrastructure projects while prioritizing safety on job sites. With $350 million in funding, we are rapidly addressing America’s increasing demand for housing, data centers, manufacturing facilities, and countering the labor shortages in the construction sector.This is where innovative algorithms integrate with hands-on engineering. You will work alongside industry experts and top-tier engineers to tackle complex physical-world challenges that simulations alone cannot solve. If you are eager to leverage cutting-edge technology to address significant issues alongside a talented team, we invite you to join us.The Onboard Infrastructure team is tasked with developing the foundational software and middleware for our onboard computer and safety controller. We build our entire stack in Rust, from board bring-up to application development.We are seeking a Senior or Staff Software Engineer to architect, develop, and optimize the core software for our onboard autonomy computer, ensuring our autonomy stack is built on a secure, deterministic, and highly optimized foundation.Your Responsibilities:Architect and maintain the embedded Linux stack for our NVIDIA Jetson platform, which includes board bring-up, kernel configuration, and OS customization.Develop and optimize low-level drivers for high-bandwidth sensors such as cameras and LiDARs, ensuring low-latency, efficient data ingestion.Implement essential system services like OTA updates, secure provisioning, telemetry, and system health monitoring.Manage Linux userspace configuration, including device management, networking, process management, and time synchronization.Enhance system performance across CPU and GPU, utilizing CUDA where applicable.Secure the platform for mixed-criticality real-time workloads through PREEMPT_RT, process isolation, and adherence to security best practices.

ABOUT BASETENAt Baseten, we empower the world's leading AI firms—such as Cursor, Notion, and OpenEvidence—by delivering mission-critical inference solutions. Our unique blend of applied AI research, robust infrastructure, and user-friendly developer tools enables AI pioneers to effectively deploy groundbreaking models. With our recent achievement of a $300M Series E funding round supported by esteemed investors like BOND and IVP, we're on an exciting growth trajectory. Join our dynamic team and contribute to the platform that drives the next generation of AI products.THE ROLEWe are looking for an experienced Senior GPU Kernel Engineer to join our innovative team at the forefront of AI acceleration. In this role, your programming expertise will directly enhance the performance of cutting-edge machine learning models. You'll be responsible for developing highly efficient GPU kernels that optimize computational processes, allowing for transformative AI applications.You'll thrive in a fast-paced, intellectually challenging environment where your technical skills are pivotal. Your contributions will directly affect production systems that serve millions of users across various platforms. This position offers exceptional opportunities for career advancement for engineers enthusiastic about low-level optimization and impactful systems engineering.EXAMPLE INITIATIVESAs part of our Model Performance team, you will engage in projects like:Baseten Embeddings Inference: The quickest embeddings solution availableThe Baseten Inference StackEnhancing model performance optimizationRESPONSIBILITIESCore Engineering ResponsibilitiesDesign and develop high-performance GPU kernels for essential machine learning operations, including matrix multiplications and attention mechanisms.Collaborate with cross-functional teams to drive performance improvements and implement optimizations.Debug and refine kernel code to achieve maximal efficiency and reliability.Stay abreast of the latest advancements in GPU technology and machine learning frameworks.

At Sciforium, we are at the forefront of AI infrastructure, innovating next-generation multimodal AI models and a proprietary high-efficiency serving platform. With substantial funding and direct collaboration from AMD, supported by their engineers, our team is rapidly expanding to develop the complete stack that powers cutting-edge AI models and real-time applications.About the RoleWe are on the lookout for a talented GPU Kernel Engineer who is eager to explore and maximize performance on modern accelerators. In this role, you will be responsible for designing and optimizing custom GPU kernels that drive our advanced large-scale AI systems. You will navigate the hardware-software stack, engaging in low-level kernel development and integrating optimized operations into high-level machine learning frameworks for large-scale training and inference.This position is perfect for someone who excels at the intersection of GPU programming, systems engineering, and state-of-the-art AI workloads, and aims to contribute significantly to the efficiency and scalability of our machine learning platform.Key ResponsibilitiesDevelop, implement, and enhance custom GPU kernels utilizing C++, PTX, CUDA, ROCm, Triton, and/or JAX Pallas.Profile and fine-tune the end-to-end performance of machine learning operations, particularly for large-scale LLM training and inference.Integrate low-level GPU kernels into frameworks such as PyTorch, JAX, and our proprietary internal runtimes.Create performance models, pinpoint bottlenecks, and deliver kernel-level enhancements that significantly boost AI workloads.Collaborate with machine learning researchers, distributed systems engineers, and model-serving teams to optimize computational performance across the entire stack.Engage closely with hardware vendors (NVIDIA/AMD) and stay updated on the latest GPU architecture and compiler/toolchain advancements.Contribute to the development of tools, documentation, benchmarking suites, and testing frameworks ensuring correctness and performance reproducibility.Must-Haves5+ years of industry or research experience in GPU kernel development or high-performance computing.Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a related discipline.Strong programming proficiency in C++, Python, and familiarity with machine learning frameworks.

Join Our Team at KernelAt Kernel, we are revolutionizing the way developers interact with the digital world through our innovative platform, offering Lightning-Fast Browsers-as-a-Service for seamless browser automation and advanced web agents. Our cutting-edge API and MCP server empower developers to effortlessly launch browsers in the cloud, eliminating the complexities of infrastructure management.Our serverless browser platform takes the hassle out of autoscaling, reliability, and observability, allowing developers to concentrate on their agents' functionality rather than the underlying processes. Kernel transforms AI into a practical and impactful tool, enabling developers to deploy agents that can genuinely engage with online environments.Trusted by industry leaders such as Cash App and Rye for applications ranging from comprehensive research to QA automation and real-time web analysis, we have successfully raised $22M from prominent investors including Accel, YCombinator, and others.With just one line of code, any web agent can be deployed to our cloud—what happens next is up to you. If you are passionate about creating essential infrastructure for the future of AI applications, we would love to connect.

About KernelKernel is an innovative developer platform that delivers Lightning-Fast Browsers-as-a-Service for browser automation and web agent deployment. Our API and MCP server empower developers to effortlessly launch cloud-based browsers without the hassle of infrastructure management.Our serverless browser solution takes care of the complexities: autoscaling, dependable browser infrastructure, observability, and intricate web interactions, allowing developers to concentrate on their agents' functionality rather than the underlying technology. Kernel brings AI to life, enabling developers to create agents that genuinely engage with the digital landscape.Our platform is trusted by teams at Cash App, Rye, and many others for various tasks including in-depth research, QA automation, and real-time web analysis. We recently secured $22M in funding from notable investors such as Accel, YCombinator, Vercel, Paul Graham, Solomon Hykes (Docker), David Cramer (Sentry), and Charlie Marsh (Astral).With just a single line of code, you can deploy any web agent to our cloud infrastructure. If you are passionate about developing essential infrastructure for the future of AI applications, we would love to connect with you.

About KernelKernel is a cutting-edge developer platform that offers Lightning-Fast Browsers-as-a-Service tailored for browser automation and web agent creation. Our API and MCP server enable developers to seamlessly launch browsers in the cloud without the hassle of infrastructure management.Our serverless browser platform takes care of the complex tasks: autoscaling reliable browser infrastructure, ensuring observability, and managing the intricate details of web interactions, allowing developers to concentrate on their agent functionalities rather than the underlying processes. Kernel brings AI to life, making it practical and powerful, empowering developers to deploy agents that can effectively engage with the digital landscape.We are trusted by teams at Cash App, Rye, and numerous others for diverse applications like in-depth research, QA automation, and real-time web analysis. We have successfully secured $22M in funding from notable investors including Accel, YCombinator, Vercel, Paul Graham, Solomon Hykes (Docker), David Cramer (Sentry), Charlie Marsh (Astral), among others.With just one line of code, you can deploy any web agent to our cloud. The rest is in your hands. If you're passionate about developing critical infrastructure for the next generation of AI applications, we would love to connect.

About KernelKernel is a cutting-edge developer platform that offers Lightning-Fast Browsers-as-a-Service for browser automations and web agents. Our API and MCP server empower developers to effortlessly launch browsers in the cloud without the hassle of managing infrastructure.Our serverless browser platform takes care of the complex aspects: autoscaling reliable browser infrastructure, observability, and intricate web interactions, enabling developers to concentrate on the functionality of their agents rather than the underlying details. Kernel transforms AI into a tangible, practical, and powerful tool, allowing developers to deploy agents capable of genuine interaction with the digital landscape.We pride ourselves on being trusted by teams at Cash App, Rye, and numerous others for deep research, QA automation, and real-time web analysis. We have successfully secured $22M in funding from top investors including Accel, YCombinator, Vercel, Paul Graham, Solomon Hykes (Docker), David Cramer (Sentry), Charlie Marsh (Astral), and more.With just one line of code, you can deploy any web agent to our cloud. The rest is in your hands. If you are passionate about building essential infrastructure for the next wave of AI applications, we would love to hear from you.About the RoleAs a Product Engineer at Kernel, you will be a full-stack engineer who values product development as much as coding. You possess the ability to translate your strong product instincts into code, ranging from pixel-perfect UI decisions to backend API architecture. You proactively contribute to the specification process rather than waiting for one to be provided.You will collaborate closely with our co-founders to define product direction, deliver full-stack features from end to end, and ensure that Kernel maintains its polished yet powerful appearance.Your ResponsibilitiesLead the full-stack implementation of user-facing product surfaces: dashboard, onboarding, website, and core product functionalities.Influence the product roadmap by integrating customer feedback, analyzing usage patterns, and leveraging your own insights into developer needs.Enhance developer experience across our SDK, documentation, CLI, and API, delivering the kind of seamless experience that makes developers exclaim, 'this just works.'Rapidly prototype and iterate, bringing features from concept to production with minimal oversight.Help shape the standards for building a superior developer product at Kernel.Your QualificationsYou are comfortable taking ownership of features from frontend to backend, demonstrating a holistic understanding of product development.A strong passion for creating seamless user experiences and an ability to translate product vision into functional code.Experience working in a fast-paced environment with a focus on agile methodologies.

At Magic, our goal is to develop safe AGI that propels humanity forward by addressing some of the most pressing challenges we face. We are committed to harnessing the power of automated research and code generation to enhance models and improve alignment in ways that surpass human capabilities. Our innovative methodology integrates cutting-edge pre-training, domain-specific reinforcement learning, ultra-long context, and advanced inference-time computing.Role OverviewAs a Kernel Engineer, you will be responsible for the design, implementation, and maintenance of high-performance kernels, aiming to optimize throughput and minimize latency during both training and inference processes.Magic's extended context windows present unique kernel optimization challenges, particularly regarding memory efficiency, data movement, and sustained throughput.Key ResponsibilitiesDesign and develop kernels that facilitate high-performance long-context functionality.Take ownership of kernel design, implementation, deployment, and ensure production reliability.Emphasize robustness, thorough testing, and functional accuracy while striving for optimal performance.Assess the feasibility of porting Magic’s compute kernels to various hardware platforms.Collaborate with the training, inference, and reinforcement learning teams to co-design kernels.Explore our work through the Magic-Attention, presented at GTC 2026.QualificationsExperience in low-level programming for AI accelerators, including NVIDIA Blackwell or Google TPUs.Proficient in developing and optimizing GPU kernels using frameworks such as NCCL, MSCCLPP, CUTLASS, CuTeDSL, Triton, Quack, and Flash Attention.

Join Zyphra as a Research Engineer specializing in AI Performance and Kernel Optimization. In this role, you will work at the forefront of AI technologies, developing and optimizing kernel solutions that enhance the performance of our systems. You will collaborate with cross-functional teams, leveraging your expertise to drive innovation and efficiency.

About AnthropicAt Anthropic, our mission is to pioneer safe, interpretable, and controllable AI systems that enhance the well-being of users and society. Our rapidly expanding team comprises dedicated researchers, engineers, policy experts, and business leaders united in the pursuit of developing beneficial AI technologies.We are looking for a highly skilled Linux OS and System Programming Specialist to join our Infrastructure team. In this pivotal role, you will focus on accelerating and fine-tuning our virtualization and VM workloads that are essential for our AI infrastructure. Your deep knowledge in low-level system programming, kernel optimization, and virtualization technologies will play a key role in scaling our compute infrastructure effectively and reliably for training and deploying cutting-edge AI models.

At Inferact, we are on a mission to establish vLLM as the premier AI inference engine, significantly enhancing the speed and reducing the cost of AI inference. Our founders, the visionaries behind vLLM, have spent years bridging the gap between advanced models and cutting-edge hardware.About the RoleWe are seeking a skilled performance engineer dedicated to maximizing the computational efficiency of modern accelerators. In this role, you'll develop kernels and implement low-level optimizations that position vLLM as the fastest inference engine globally. Your contributions will be pivotal as your code will execute across a broad spectrum of hardware accelerators, from NVIDIA GPUs to the latest silicon innovations. You'll collaborate closely with hardware vendors to ensure we fully leverage the capabilities of each new generation of chips.

At Thinking Machines Lab, our ambition is to enhance human potential by advancing collaborative general intelligence. We envision a future where individuals have the tools and knowledge to harness AI for their distinct requirements and aspirations.Our team comprises dedicated scientists, engineers, and innovators who have contributed to some of the most renowned AI products, including ChatGPT and Character.ai, along with open-weight models like Mistral, and influential open-source projects such as PyTorch, OpenAI Gym, Fairseq, and Segment Anything.About the RoleWe are seeking an Infrastructure Research Engineer to architect, optimize, and sustain the computational frameworks that facilitate large-scale language model training. You will create high-performance machine learning kernels (e.g., CUDA, CuTe, Triton), enable effective low-precision arithmetic operations, and enhance the distributed computing infrastructure essential for training expansive models.This position is ideal for an engineer who thrives in close collaboration with hardware and research disciplines. You will partner with researchers and systems architects to merge algorithmic design with hardware efficiency. Your responsibilities will include prototyping new kernel implementations, evaluating performance across various hardware generations, and helping to establish the numerical and parallelism strategies crucial for scaling next-generation AI systems.Note: This is an evergreen role that remains open continuously for expressions of interest. We receive numerous applications, and there may not always be an immediate opportunity that aligns with your qualifications. However, we encourage you to apply, as we regularly assess applications and will reach out as new positions become available. You are also welcome to reapply after gaining additional experience, but please refrain from applying more than once every six months. Additionally, you may notice postings for specific roles catering to particular projects or team needs. In such cases, you are encouraged to apply directly alongside this evergreen listing.What You’ll DoDesign and develop custom ML kernels (e.g., CUDA, CuTe, Triton) for key LLM operations such as attention, matrix multiplication, gating, and normalization, optimized for contemporary GPU and accelerator architectures.Conceptualize compute primitives aimed at alleviating memory bandwidth bottlenecks and enhancing kernel compute efficiency.Collaborate with research teams to synchronize kernel-level optimizations with model architecture and algorithmic objectives.Create and maintain a library of reusable kernels and performance benchmarks that serve as the foundation for internal model training.Contribute to the stability and scalability of our infrastructure, ensuring it meets the growing demands of AI development.

Fastly operates an edge cloud platform that processes, serves, and protects applications at the Internet’s edge, close to end users. The platform is programmable and supports agile software development. Well-known brands such as GitHub, Yelp, Paramount, and JetBlue rely on Fastly’s services. Fastly’s mission is to build a more trustworthy Internet. Key Dates Posting Open Date: April 23, 2026 Anticipated Posting Close Date: May 7, 2026 The posting may close early depending on applicant volume. Role overview The Director of Engineering - Edge Linux Networking leads Fastly’s Kernel engineering team. This group is responsible for the performance and stability of the low-latency data path through the Linux kernel and XDP, supporting all customer traffic. The team maintains Fastly’s kernel alignment with upstream releases and both uses and contributes to new Linux technologies. This role also oversees support for the hardware platform and manages the lifecycle of OCI containers and Linux Operating System Distributions. Strong leadership is essential to maintain the stability of Fastly’s Edge stack and deliver high-quality service to customers. Locations Denver, CO New York City, NY San Francisco, CA

At Databricks, we are dedicated to empowering data teams to tackle the world's most challenging problems, from detecting security threats to advancing cancer drug development. We achieve this by offering the premier data and AI platform, allowing our customers to concentrate on their mission-critical challenges. The Mosaic AI organization assists companies in developing AI models and systems utilizing their own data, employing technologies that range from training large language models (LLMs) from the ground up to employing advanced retrieval methods for enhanced generation. We pride ourselves on pushing the boundaries of science and operationalizing our innovations. Mosaic AI believes that a company’s AI models hold intrinsic value, akin to any other core intellectual property, and that superior AI models should be accessible to all. Job Overview As a research engineer in the Scaling team, you will stay abreast of the latest advancements in deep learning and pioneer new methodologies that surpass the current state of the art. You will collaborate with a diverse team of researchers and engineers, sharing insights and expertise. Most importantly, you will be passionate about our customers, striving to ensure their success in implementing cutting-edge LLMs and AI systems by translating our scientific knowledge into practical applications. Your Impact Enhance performance through innovative optimization techniques, including kernel fusion, mixed precision, memory layout optimization, tiling strategies, and tensorization tailored for training-specific patterns. Design, implement, and optimize high-performance GPU kernels for training workloads, including attention mechanisms, custom layers, gradient computations, and activation functions, specifically for NVIDIA architectures. Create and implement distributed training frameworks for large language models, incorporating parallelism strategies (data, tensor, pipeline, ZeRO-based) and optimized communication patterns for gradient synchronization and collective operations. Profile, debug, and optimize comprehensive training workflows to pinpoint and resolve performance bottlenecks, utilizing memory optimization techniques such as activation checkpointing, gradient sharding, and mixed precision training.

At Gimlet Labs, we are pioneering the first heterogeneous neocloud tailored for AI workloads. As the demand for AI systems grows, traditional infrastructure faces significant limitations in terms of power, capacity, and cost. Our innovative platform addresses these challenges by decoupling AI workloads from the hardware, intelligently partitioning tasks, and directing each component to the most suitable hardware for optimal performance and efficiency. This method allows for the creation of heterogeneous systems that span multiple vendors and generations of hardware, including the latest cutting-edge accelerators, achieving substantial improvements in performance and cost-effectiveness.Building upon this robust foundation, Gimlet is developing a production-grade neocloud designed for agentic workloads. Our customers can effortlessly deploy and manage their workloads with stable, production-ready APIs, eliminating the complexities of hardware selection, placement, or low-level performance optimization.We collaborate with foundational labs, hyperscalers, and AI-native companies to drive real production workloads capable of scaling to gigawatt-class AI data centers.We are currently seeking a dedicated Member of Technical Staff specializing in kernels and GPU performance. In this role, you will work closely with accelerators and execution hardware to extract maximum performance from AI workloads across diverse and rapidly evolving platforms. You will analyze low-level execution behaviors, design and optimize kernels, and ensure consistent performance across both established and emerging hardware.This position is perfect for engineers who thrive on deep performance analysis, enjoy exploring hardware trade-offs, and are passionate about transforming theoretical peak performance into tangible real-world outcomes.

Join Promise as a Software Engineering Lead in the heart of San Francisco, where you will play a pivotal role in driving innovative software solutions. You’ll be responsible for leading a talented team of engineers to design, develop, and implement high-quality software products that meet the needs of our clients. This is an exciting opportunity to make a significant impact in a dynamic and growing company.

Join our dynamic team at MaximusTribe as a Lead Software Engineer / Tech Lead Manager in Growth. In this fully remote role, you will be at the forefront of driving innovative software solutions that propel our company's growth. You will lead a team of talented engineers, fostering a culture of collaboration and excellence while developing cutting-edge applications that impact our users positively.