Software Engineer - GPU Kernels

About Baseten Baseten powers mission‑critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting‑edge models into production. We’re growing quickly and recently raised our $300M SeriesE, backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction. The Role We’re seeking a GPU Kernel Engineer to join our team at the cutting edge of AI acceleration. In this role you will craft the foundation that powers modern AI workloads, optimizing every microsecond of computation to enable breakthrough applications. Example Initiatives 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) Requirements 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 Benefits Competitive compensation, including meaningful equity. 100% coverage of medical, dental, and vision insurance for employee and dependents Flexible PTO policy including company‑wide Winter Break (offices closed from Christmas Eve to New Year’s Day) Paid parental leave Fertility and family‑building stipend through Carrot Company‑facilitated 401(k) Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. EEO Statement At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable). Compensation Range: $180K - $360K #J-18808-Ljbffr