GPU Kernel Engineer
San Francisco
⚠️ We'll shut down after Aug 1st - try foo🦍 for all jobs in tech ⚠️
Full Time Mid-level / Intermediate USD 185K - 250K
Baseten
Effortlessly serve optimized open source & custom models on the fastest, most reliable model delivery networkABOUT BASETEN
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.
THE ROLE
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:
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
1–5 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.
Tags: APIs Architecture AWS CUDA Engineering GPU Machine Learning ML models Open Source Research Security Spark
Perks/benefits: Career development Competitive pay Conferences Flex vacation Startup environment
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.