Kernel jobs

Systems/Software Engineer II (Platforms Developer - C/C++, Linux kernel, Device Drivers) Bengaluru, Karnātaka, India Embrace the role of a Systems Software Engineer II and help design, develop, and maintain cutting-edge platforms for next-generation networking. Collaborate with hardware and QA teams, work with C/C++, Linux, and device drivers, and drive innovation in embedded and cloud solutions. Grow your career with HPE's global technology team.

Leader, Software Engineering | C, C++, BSP, SONiC, Device Driver, Linux, Kernel, People Leader | 12+ years Bangalore, India We are looking for a Senior Manager within the Common Hardware Group to lead a high-performing team of software engineers at Cisco. This role involves defining technical strategies and mentoring top-tier engineering talent while ensuring software solutions provide a competitive advantage in the market.

Staff Software Engineer in Test (SDET) Santa Clara, Santa Clara, Ca, Ca, United States At d-Matrix , we are focused on unleashing the potential of generative AI to power the transformation of technology. We are at the forefront of software and hardware innovation, pushing the boundaries of what is possible. Our culture is one of respect and collaboration. We value humility and believe in direct communication. Our team is inclusive , and our differing perspectives allow for better solutions. We are seeking individuals passionate about tackling challenges and are driven by execution. Ready to come find your playground? Together , we can help shape the endless possibilities of AI. Location: Hybrid-Santa Clara, CA headquarters, 3-5 days/week onsite Team: Kernels | Reports to: Engineering Manager, Kernels Cross-functional interface: QA / Test Engineering About the Role We are looking for a Staff Software Engineer, Test & Validation - AI Kernels to embed within our Kernels team and own the quality engineering function for our AI compute software stack. You will design and build the test infrastructure, validation frameworks, and automated verification pipelines that ensure correctness, performance, and reliability of software kernels running on next-generation AI hardware. You will serve as the primary quality interface between the Kernels team and the broader QA organization, driving alignment on test strategy, coverage, and release readiness. This is a high-impact, deeply technical role that requires both strong software engineering skills and a rigorous quality mindset. You will work alongside compiler engineers, ML software engineers, and hardware

Software Engineering Technical Leader | C, C++, BSP, SONiC, Device Driver, Linux, Kernel | 12 + years Bangalore, India Join our team as a Senior Software Engineering Technical Leader and drive innovation in embedded systems for Cisco's advanced network products. Lead the development of device drivers, bios, and diagnostics, collaborating with cross-functional teams to shape the future of AI and ML. Grow your expertise in a dynamic, global environment with cutting-edge technology.

Principal Machine Learning Engineer, Accelerated Apache Spark US, CA, Santa Clara posted: Posted 22 Days Ago

Machine Learning Mountain View, CA, US, Redmond, WA, US, New York, NY, US

LINUX_PaaS Engineer GBR - GLS - GLOUCESTER posted: Posted 30+ Days Ago

Kernel/OS Engineer, AWS EC2 Nitro Operating System Seattle, Washington, USA AWS EC2 Nitro powers the world's largest, fastest-growing, and most feature-rich compute cloud. Built from the ground up for virtualization at global scale, Nitro is a fully custom stack of hardware, firmware, and software that enables EC2 to support Intel, AMD, and AWS's own Graviton processors - while setting industry benchmarks for security and performance. With our Nitro System, we break apart traditional hypervisor functions like CPU virtualization, storage, and networking, and offload them to dedicated hardware and software. This enables us to deliver practically all of the resources of a server to customer instances, innovate faster, increase security, deliver new instance types, and reduce customer cost. The Nitro Linux team owns the secure, embedded Linux environment at the heart of this system. We build and maintain the operating system that integrates with the Nitro control plane and powers live updates, metrics collection, core dump handling, and system health monitoring across AWS's global infrastructure. Linux, ash, C, lua, Rust - join us for embedded software systems at cloud scale! Key job responsibilities - Research, design, and implement Linux kernel changes to meet business requirements - Drive kernel development for next-generation EC2 compute platforms - Bring up Linux on new hardware platforms and custom silicon - Debug complex, system-level, multi-component issues across layers from kernel to application - Profile system performance and drive optimizations across the software stack - Develop tooling for performance characterization, qualification, and deployment - Deliver production-quality code

Dir, Machine Learning Eng San Jose posted: Posted 30+ Days Ago

Principal Software Engineer - Linux Kernel Performance United States You can make a significant impact on Akamai's business. A successful candidate will seek challenges, are passionate for learning, and have demonstrated ability to pose and solve difficult problems. The job requires solid system design, solid programming and debugging skills, an obsession with code quality, and independence. You must have a passion to get things done quickly and correctly.

Machine Learning Engineer, Platform Architecture Cupertino, United States of America At Apple, our Platform Architecture group is responsible for connecting our hardware and software into one unified system! You'll collaborate with engineers across Apple to design how our technologies work in unison, drive development of our renowned system-on-a-chip architecture and develop forward-looking prototype systems. Our team works at the intersection of ML applications and Apple silicon architecture. We collaborate with SoC/IP architecture, system, software, and algorithm teams to develop integrated, highly optimized solutions for machine learning applications. In this role, you will explore different ways of mapping ML workloads to Apple silicon and develop performance models/simulations. Your work will inform and validate architecture decisions. You will gain insights on how to make workloads run efficiently on our SoCs and communicate what we learn to software and algorithm teams. Create optimized implementations of ML workloads on Apple silicon including Neural Engine, GPU, and CPU. Collaborate with IP and SoC architecture teams to develop performance models and simulations of future hardware. Conduct performance studies to inform and validate architecture decisions. Collaborate with system teams to create high-level performance models of emerging ML techniques and analyze system architecture trade-offs. Minimum Qualifications: Bachelor's degree Ability to program in C/C++ and/or Python Knowledge of computer architecture fundamentals Domain knowledge in at least one hardware IP: ML HW accelerators or processing units such as GPU, image/video, CPUs, or similar Preferred Qualifications: MS or PhD in EE/CE/CS or related field, or 3+ years of relevant experience Experience

Senior Engineer / Technical Lead (Linux BSP) Hyderabad, Telangāna, India Join our team as a Senior Engineer / Technical Lead (Linux BSP) and drive the design and development of real-time embedded and mobile software. Leverage your expertise in Linux device drivers, kernel programming, and embedded systems to deliver innovative solutions. Collaborate with cross-functional teams and shape the future of embedded technology.

CLOUD MACHINE LEARNING ENGINEER Pune, Maharashtra, India

Image Processing Engineer (C++/Linux) US, California, Santa Clara posted: Posted 30+ Days Ago

Technical Leader - C/C++, Device Driver, Kernel, Multithreading, Embedded Systems - 10 to 13 years - Bangalore Bangalore, India Join our team as a Senior Embedded Systems Technical Leader and drive innovation in hardware and software for Cisco's next-generation network products. Leverage your expertise in C/C++, device drivers, and embedded systems to architect, develop, and validate advanced solutions. Collaborate with top engineers and shape the future of AI and network infrastructure.

Power Platform/Copilot Solution Engineer Tokyo, Tokyo, JP

Senior Engineer - Linux BSP (Solutions) Noida, Uttar Pradesh, India Join our team as a Senior Engineer - Linux BSP and drive the design and development of real-time embedded and mobile software solutions. Leverage your expertise in Linux device drivers, kernel programming, and embedded systems to deliver high-quality solutions. Collaborate with cross-functional teams and contribute to innovative projects in a dynamic environment.

Staff Software Engineer, Linux Kernel Memory Management Sunnyvale, CA, USA Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. The AI and Infrastructure team is redefining what's possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide. We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs,

Senior Security Software Engineer, Linux Kernel Security - Nodes & Sensors Zürich, CH About Anthropic Anthropic'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. About the role Anthropic's Detection Platform team is building the next-generation Linux endpoint security system that protects our AI research and production infrastructure. We're looking for a senior engineer to architect and implement node-layer security sensors, develop kernel-based detection systems for ML workloads, and build tooling that leverages Claude to transform how security operations work. This is a high-ownership role on a small team. You'll design systems that run across our rapidly growing fleet with minimal performance overhead, partner closely with security and infrastructure engineers, and help shape the technical direction of endpoint detection at Anthropic. Key responsibilities - Build kernel-level security detections for our AI platform, including eBPF-based sensors for Linux endpoints - Design and implement scalable data pipelines for ingesting and processing security telemetry across our infrastructure - Architect monitoring solutions for production systems that minimize performance impact on ML workloads - Prototype new security tooling and analytics capabilities, including applications of Claude to detection and response workflows - Partner with security and infrastructure teams to translate requirements into reliable, maintainable systems - Contribute to the growth of the Security team through

Software Engineer, Accelerators San Francisco, California, United States About the Team The Kernels team at OpenAI builds the low-level software that accelerates our most ambitious AI research. We work at the boundary of hardware and software, developing high-performance kernels, distributed system optimizations, and runtime improvements to make large-scale training and inference more efficient. Our work enables OpenAI to push the limits by ensuring models - from LLMs to recommender systems - to run reliably on advanced supercomputing platforms. That includes adapting our software stack to new types of accelerators, tuning system performance end-to-end, and removing bottlenecks across every layer of the stack. About the Role On the Accelerators team, you will help OpenAI evaluate and bring up new compute platforms that can support large-scale AI training and inference. Your work will range from prototyping system software on new accelerators to enabling performance optimizations across our AI workloads. You'll work across the stack, collaborating with both hardware and software aspects - working on kernels, sharding strategies, scaling across distributed systems, and performance modeling. You'll help adapt OpenAI's software stack to non-traditional hardware and drive efficiency improvements in core AI workloads. This is not a compiler-focused role, rather bridging ML algorithms with system performance - especially at scale. In this role, you will: - Prototype and enable OpenAI's AI software stack on new, exploratory accelerator platforms. - Optimize large-scale model performance (LLMs, recommender systems, distributed AI workloads) for diverse hardware environments. - Develop kernels, sharding mechanisms, and system scaling strategies tailored to

Software Engineering Manager, ML Kernel Performance, AWS Neuron, Annapurna Labs Cupertino, California, USA The Annapurna Labs team at Amazon Web Services (AWS) builds AWS Neuron, the software development kit used to accelerate deep learning and GenAI workloads on Amazon's custom machine learning accelerators, Inferentia and Trainium. The Acceleration Kernel Library team is at the forefront of maximizing performance for AWS's custom ML accelerators. Working at the hardware-software boundary, our engineers craft high-performance kernels for ML functions, ensuring every FLOP counts in delivering optimal performance for our customers' demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what's possible in AI acceleration. The AWS Neuron SDK, developed by the Annapurna Labs team at AWS, is the backbone for accelerating deep learning and GenAI workloads on Amazon's Inferentia and Trainium ML accelerators. This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch, enabling unparalleled ML inference and training performance. As part of the broader Neuron Compiler organization, our team works across multiple technology layers - from frameworks and compilers to runtime and collectives. We not only optimize current performance but also contribute to future architecture designs, working closely with customers to enable their models and ensure optimal performance. This role offers a unique opportunity to work at the intersection of machine learning, high-performance computing, and distributed architectures, where you'll help shape the future of AI acceleration technology This is an opportunity to work on cutting-edge products

Linux Embedded Software Engineer Poland Who We Are Verkada is transforming how organizations protect their people and places with an integrated, privacy-sensitive AI-powered platform that includes solutions for video security, access control, air quality sensors, alarms, intercoms, and visitor management. We've got serious momentum in the market: more than 30,000 customers (including 100+ of the Fortune 500), a $5.8B valuation , more than $1 billion in annualized bookings, and backing from CapitalG, Sequoia Capital, General Catalyst, Felicis Ventures, Next47 and more. Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the center of it. You can look at all kinds of communities to see our platform's impact in the world. It's the retailer that uses our agentic AI to deter theft before it happens. The warehouse that uses AI-powered alerts to make sure its team is protected on the floor with proper PPE. The school that's alerted to a threat in real-time and triggers a lockdown in seconds, not minutes. We're rapidly scaling this impact: today, more than 2 million Verkada devices are deployed across 170+ countries. About the Role We're focused on hiring embedded software engineers that understand not only the lower-level systems, but also how everything integrates together from the hardware to the UI. You'll be working closely on one side with our hardware vendors and ME/EE people, and on the other side with server and UI engineers, industrial designers, and our operations team. If you're looking for a fast-paced

Senior Applied Machine Learning Engineer - VLSI Design US, CA, Santa Clara posted: Posted 9 Days Ago

On-Device ML Infrastructure Engineer (CoreML Runtime), Graphics, Games and Machine Learning Cupertino, United States of America Imagine being at the forefront of an evolution where powerful AI meets the elegance of Apple silicon. The On-Device Machine Learning team transforms groundbreaking research into practical applications, enabling billions of Apple devices to run powerful AI models locally, privately, and efficiently. We stand at the unique intersection of research, software engineering, hardware engineering, and product development, making Apple a top destination for on-device machine learning innovation. Our team builds the essential infrastructure that enables machine learning at scale on Apple devices. This involves onboarding innovative architectures to embedded systems, developing optimization toolkits for model compression and acceleration, building ML compilers and runtimes for efficient execution, and creating comprehensive benchmarking and debugging toolchains. This infrastructure forms the backbone of Apple's machine learning workflows across Camera, Siri, Health, Vision, and other core experiences, contributing to the overall Apple Intelligence ecosystem. If you are passionate about the technical challenges of running sophisticated ML models on resource-constrained devices and eager to directly impact how machine learning operates across the Apple ecosystem, this role presents an incredible opportunity to work on the next generation of intelligent experiences on Apple platforms. We are seeking an ML Infrastructure Engineer with a specific focus on graph compilers and runtimes. If you are a highly motivated software engineer who is creative, versatile, and passionate about machine learning operator primitives, common compiler optimizations, runtimes, and system software engineering in the fast-paced and dynamic