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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # GPU Kernel Engineer - **Company:** Baseten, Inc - **Location:** San Francisco, CA, United States - **Contract:** Permanent contract - **Skills:** Adobe Flash, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, C++ (Programming Language), Program Optimization, Profiling, Nvidia CUDA, Machine Learning, Open Source Technology, Performance Tuning, Graphics Processing Unit (GPU), Model Validation, Machine Learning Operations - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/software-engineer-gpu-kernels-baseten-7172420 ## About the Role * Strong understanding of GPU architecture and programming paradigms: + Memory hierarchy (global, shared, registers, L1/L2 cache) + Thread/block/grid organization + Synchronization techniques and race condition mitigation * Proficient in C++ and GPU performance profiling tools * Knowledge of: + CUDA C++ API + Memory access patterns and bandwidth optimization + Numerical precision and quantization strategies + Modern GPU features (e.g., tensor cores, async operations) NICE TO HAVE * Experience with Transformer models and attention optimization (e.g., Flash Attention) * Familiarity with GPU kernel libraries: Cutlass, Triton, Thrust, CUB * Background in GEMM tuning and distributed/multi-GPU compute * Contributions to open-source GPU projects * Research publications or conference presentations on GPU performance ## Description We're seeking a GPU Kernel Engineer to join our team at the cutting edge of AI acceleration, where your code directly impacts the performance of state-of-the-art machine learning models. As a GPU Kernel Engineer, you'll craft the foundation that powers modern AI workloads, optimizing every microsecond of computation to enable breakthrough applications. You'll work in a fast-paced, intellectually stimulating environment where technical excellence is paramount and your contributions directly influence production systems serving millions of users across numerous products. This role offers exceptional growth potential for engineers passionate about low-level optimization and high-impact systems work. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Model Performance team: * Baseten Embeddings Inference: The fastest embeddings solution available * The Baseten Inference Stack * Driving model performance optimization RESPONSIBILITIES Core Engineering Responsibilities * Design and implement high-performance GPU kernels for key ML operations, including matrix multiplications, attention mechanisms, and mixture-of-experts routing * Write and optimize code using CUDA, PTX assembly, and architecture-specific techniques * Apply advanced performance optimization methods such as memory coalescing, warp-level programming, tensor core acceleration, and compute/memory overlap Performance & Innovation * Implement cutting-edge features like quantization (FP8/FP4), sparsity, and compute/communication overlap * Identify and resolve performance bottlenecks using tools like Nsight Systems, Nsight Compute, and Torch Profiler * Collaborate with research teams to productionize theoretical advancements Impact & Collaboration * Contribute to internal and open-source GPU libraries * Present technical contributions at industry conferences (e.g., NVIDIA GTC, AWS re:Invent) ## Related Videos - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [Accelerating Python on GPUs](https://www.wearedevelopers.com/videos/859-accelerating-python-on-gpus) - [Profiling Symfony & PHP apps with Blackfire](https://www.wearedevelopers.com/videos/265-profiling-symfony-php-apps-with-blackfire) - [CUDA Python: GPU programming for the modern developer](https://www.wearedevelopers.com/videos/100221-cuda-python-gpu-programming-for-the-modern-developer) - [A Deep Dive on How To Leverage the NVIDIA GB200 for Ultra-Fast Training and Inference on Kubernetes](https://www.wearedevelopers.com/videos/1625-a-deep-dive-on-how-to-leverage-the-nvidia-gb200-for-ultra-fast-training-and-inference-on-kubernetes) - [Accelerating Python on GPUs](https://www.wearedevelopers.com/videos/1521-accelerating-python-on-gpus) ## Related Articles - [What’s the latest in NVIDIA CUDA Python](https://www.wearedevelopers.com/magazine/568-what-s-the-latest-in-nvidia-cuda-python) - [Dev Digest 157: CUDA in Python, Gemini Code Assist and Back-dooring LLMs](https://www.wearedevelopers.com/magazine/557-dev-digest-157-cuda-in-python-gemini-code-assist-and-back-dooring-llms) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 102 - Race conditions](https://www.wearedevelopers.com/magazine/386-dev-digest-102-race-conditions) - [The Best X (Twitter) Accounts for Developers](https://www.wearedevelopers.com/magazine/294-the-best-x-twitter-accounts-for-developers) - [Dev Digest 129 - Now that's what I call private data!](https://www.wearedevelopers.com/magazine/468-dev-digest-129-now-that-s-what-i-call-private-data)