22 gpu ai kernel development engineer jobs at 9 companies in United States
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Principal GPU AI Kernel Development Engineer
San Diego, California, United States
$202k-$304k/yrOnsiteFull Time
Qualcomm Technologies, Inc.: Developing semiconductor, wireless, connectivity, automotive, AI, and computing technologies for device and enterprise customers.
6+ YOEDegree in Computer Engineering/Computer Science/Electrical Engineering (BS/MS/PhD) with 6+ years (PhD) to 8+ years (BS) of relevant engineering experience; GPU experience, technical leadership experience and interaction with senior leadership preferred.
Staff Software Development Engineer: GPU, Computer Vision, AI/ML Ops
Santa Clara, California, United States
OnsiteFull Time
AMDNASDAQ: AMD: Leader in high-performance computing, graphics, and visualization technologies.
Expert in high-performance C++ and GPU programming (HIP/CUDA), experience with LLMs and AI systems, GPU profiling and kernel optimization, and degree in CS/CE/EE.
NVIDIANASDAQ: NVDA: Computing platform for AI and accelerated graphics.
6+ YOEMasters in CS/EE or equivalent experience; 6+ years in ML/DL systems; strong Python and C/C++; experience with deep learning frameworks, inference engines, runtimes, and GPU kernel development.
GPU/AI Application System Software Engineer Intern (System Technologies and Engineering) - 2027 Summer
San Jose, California, United States
OnsiteInternship
ByteDance: Global technology specializing in AI-powered content platforms.
Pursuing a bachelor's or master's degree in computer engineering, electrical engineering, computer science, or related fields; requires OS, Linux kernel, architecture, GPU/CPU benchmarking, and Linux systems experience.
Santa Clara or Westford or Austin or Durham or Seattle
$224k-$431k/yrOnsiteFull Time
NVIDIANASDAQ: NVDA: Computing platform for AI and accelerated graphics.
12+ YOE12+ years software engineering experience in GPU computing or ML systems, strong Python or C++ skills, GPU kernel optimization (CUDA/Triton), container engineering, and LLM inference knowledge.
Hudson River Trading: Private quantitative trading firm providing liquidity across global markets and directly to financial-market clients.
2+ YOEStrong engineering skills and 2+ years building deep learning systems; experience with GPU kernels, PyTorch, JAX, XLA, CUDA Graphs, FPGA, or ASICs preferred.
Crusoe: Vertically integrated AI infrastructure and energy.
Bachelor's, master's, or Ph.D. in a related field; production coding experience in Python or C++; LLM inference optimization, serving frameworks, kernel profiling, GPU, AI/ML pipeline, and communication skills.
Sr. System Development Engineer, Edge & High Performance Accelerator Servers for AI/ML
Austin or Seattle or Cupertino
$151k-$235k/yrOnsiteFull Time
AmazonNASDAQ: AMZN: Multinational technology focused on e-commerce and cloud computing.
6+ YOE6+ years systems/software development and systems design experience; strong programming in C++, C#, Java, Python, Golang, PowerShell, or Ruby; Linux/Unix experience; experience building reliable, scalable automation, diagnostics, and CI/CD for server fleets.
C++, C#, Java, Python, Golang, PowerShell, Ruby, Linux, Linux kernel, CI/CD, BMC/IPMI, PCIe, NVMe, GPU, ARM, x86
Software Engineer, AI Kernels & Performance Optimization — MTIA Software
Bellevue or Menlo Park or New York City
$184k-$257k/yrOnsiteFull Time
MetaNASDAQ: META: Builds technologies that help people connect, find communities, and grow businesses.
6+ YOEBachelor's degree or equivalent practical experience; 6+ years in HPC, accelerator kernels, compiler backends, or systems performance; C++ and Python proficiency; parallel architecture kernel optimization experience.
d-Matrix: Private AI infrastructure serving data centers with inference accelerators, networking, and software.
12+ YOEMS with 12+ years or PhD with 7+ years; strong computer architecture; C/C++ and Python in Linux; experience with GPUs/AI accelerators; ML workloads; hardware-software co-design; leadership.
Hewlett Packard EnterpriseNYSE: HPE: Global edge-to-cloud advancing how people live and work.
Ph.D. in Computer Science or Electrical/Computer Engineering; strong distributed systems, HPC, AI workloads; programming in C/C++, Python; Linux kernel, Open vSwitch; CUDA, PyTorch, Kubernetes; network protocols.