Research Engineer, Infrastructure, Kernels
Thinking Machines Lab3 months ago
Base Salary
$400k - $500k/yr
Responsibilities
- Design and implement custom CUDA, CuTe, and Triton kernels for core LLM operations.
- Develop compute primitives that reduce memory bandwidth bottlenecks and improve kernel efficiency.
- Collaborate with research teams to align kernel optimization with model architecture and algorithmic goals.
- Build and maintain reusable kernel libraries and performance benchmarks for internal model training.
- Improve infrastructure stability, scalability, reproducibility, precision consistency, and compute utilization.
- Share technical insights through internal talks, technical papers, or open-source contributions.
Requirements
- Bachelor’s degree or equivalent experience in computer science, electrical engineering, statistics, machine learning, physics, robotics, or a similar field.
- Strong engineering skills with the ability to write performant, maintainable code and debug complex codebases.
- Understanding of deep learning frameworks such as PyTorch and JAX and their underlying system architectures.
- Proficiency in CUDA, CuTe, Triton, or other GPU programming frameworks.
- Ability to analyze, profile, and optimize compute-intensive workloads.
- Preferred qualifications include experience with large-scale language models, infrastructure productivity improvements, deep learning kernel tuning, tensor or pipeline parallelism, distributed data processing, low-precision formats, compiler stacks, open-source GPU or ML systems, numerical optimization, communication-efficient training, or scalable AI infrastructure.
- Ability to collaborate across teams, take initiative, and work with cross-functional partners and subject matter experts.
Benefits
- Based in San Francisco, California.
- Evergreen role reviewed continuously on an ongoing basis; applicants are asked not to reapply more than once every six months.
- Offers health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.
Tech Stack
Categories
About Thinking Machines Lab
Thinking Machines Lab develops AI and generative AI software and conducts applied research to help organizations make data-driven decisions. The company builds products and data science solutions for enterprise use cases, pairing foundational models with practical tooling and services across industries. It is privately held and headquartered in San Francisco.