Research Engineer, Infrastructure, Numerics
Thinking Machines Lab3 months ago
Base Salary
$400k - $500k/yr
Responsibilities
- Design and optimize distributed training infrastructure for large-scale LLMs across multi-GPU and multi-node setups.
- Implement and evaluate low-precision numerics such as BF16, MXFP8, and NVFP4.
- Develop kernels and communication primitives using hardware support for mixed- and low-precision arithmetic.
- Collaborate with research teams to co-design model architectures and training recipes for emerging numeric formats and stability constraints.
- Prototype and benchmark data, tensor, and pipeline parallelism with precision-adaptive computation and quantized communication.
- Contribute to internal orchestration and monitoring systems for efficient, reproducible distributed experiments.
- Publish and share technical learnings through internal documentation, open-source libraries, or technical reports.
Requirements
- Bachelor’s degree or equivalent experience in computer science, electrical engineering, statistics, machine learning, physics, robotics, or a similar field.
- Understanding of deep learning frameworks and their underlying system architectures, including PyTorch or JAX.
- Strong engineering ability to write performant, maintainable code and debug complex codebases involving floating-point numerics, low-precision arithmetic, and distributed systems.
- Ability to collaborate across teams and take initiative to deliver work across different technology stacks.
- Familiarity with distributed frameworks such as PyTorch/XLA, DeepSpeed, or Megatron-LM is preferred.
- Experience with FP8, INT8, or block-floating-point formats and their numerical trade-offs is preferred.
- Contributions to open-source deep learning infrastructure, publications, patents, or projects related to numerical optimization, communication-efficient training, or large-model systems are preferred.
- Experience training and supporting large-scale AI models or improving research productivity through infrastructure design is preferred.
Benefits
- Annual salary range of $400,000–$500,000 USD, depending on background, skills, and experience.
- Generous health, dental, and vision benefits.
- Unlimited paid time off.
- Paid parental leave.
- Relocation support as needed.
- Based in San Francisco, California.
- The company sponsors visas and is committed to working through the visa process for successful candidates, though success is not guaranteed for every candidate or role.
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.