ABOUT BASETENBaseten 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 Series E, backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction. Join us and help build the platform engineers turn to to ship AI products.THE ROLEWe’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 INITIATIVESYou'll get to work on these types of projects as part of our Model Performance team:Baseten Embeddings Inference: The fastest embeddings solution availableThe Baseten Inference StackDriving model performance optimizationRESPONSIBILITIESCore Engineering ResponsibilitiesDesign and implement high-performance GPU kernels for key ML operations, including matrix multiplications, attention mechanisms, and mixture-of-experts routingWrite and optimize code using CUDA, PTX assembly, and architecture-specific techniquesApply advanced performance optimization methods such as memory coalescing, warp-level programming, tensor core acceleration, and compute/memory overlapPerformance & InnovationImplement cutting-edge features like quantization (FP8/FP4), sparsity, and compute/communication overlapIdentify and resolve performance bottlenecks using tools like Nsight Systems, Nsight Compute, and Torch ProfilerCollaborate with research teams to productionize theoretical advancementsImpact & CollaborationContribute to internal and open-source GPU librariesPresent technical contributions at industry conferences (e.g., NVIDIA GTC, AWS re:Invent)REQUIREMENTS1–5 years of experience in CUDA developmentStrong understanding of GPU architecture and programming paradigms:Memory hierarchy (global, shared, registers, L1/L2 cache)Thread/block/grid organizationSynchronization techniques and race condition mitigationProficient in C++ and GPU performance profiling toolsKnowledge of:CUDA C++ APIMemory access patterns and bandwidth optimizationNumerical precision and quantization strategiesModern GPU features (e.g., tensor cores, async operations)NICE TO HAVEExperience with Transformer models and attention optimization (e.g., Flash Attention)Familiarity with GPU kernel libraries: Cutlass, Triton, Thrust, CUBBackground in GEMM tuning and distributed/multi-GPU computeContributions to open-source GPU projectsResearch publications or conference presentations on GPU performanceBENEFITSCompetitive compensation, including meaningful equity.100% coverage of medical, dental, and vision insurance for employee and dependentsGenerous PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)Paid parental leaveCompany-facilitated 401(k)Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.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.