Baseten
Gpu Kernel Engineer
Baseten provides the infrastructure, tooling, and expertise needed to bring great AI products to market - fast. Backed by top investors including IVP, Spark Capital, Greylock, and Conviction, we're trusted by leading AI-driven innovators like Writer, Abridge, Bland, Patreon, Descript, Retool, and Zed to deliver industry-leading performance, security, and reliability for their mission-critical workloads. With our recent $75M Series C funding, we're growing fast to make AI accessible across all products. 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. 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 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: 15 years of experience in CUDA development 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 package (Flexible PTO, 401k, covered healthcare premiums). This is a unique opportunity to be part of a rapidly growing startup in one of the most exciting engineering fields of our era. An inclusive and supportive work culture that fosters learning and growth. 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.
Baseten provides the infrastructure, tooling, and expertise needed to bring great AI products to market - fast. Backed by top investors including IVP, Spark Capital, Greylock, and Conviction, we're trusted by leading AI-driven innovators like Writer, Abridge, Bland, Patreon, Descript, Retool, and Zed to deliver industry-leading performance, security, and reliability for their mission-critical workloads. With our recent $75M Series C funding, we're growing fast to make AI accessible across all products. 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. 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 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: 15 years of experience in CUDA development 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 package (Flexible PTO, 401k, covered healthcare premiums). This is a unique opportunity to be part of a rapidly growing startup in one of the most exciting engineering fields of our era. An inclusive and supportive work culture that fosters learning and growth. 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.