Research Engineer, Infrastructure, Numerics
Thinking Machines Lab · San Francisco
CHECKED 13H AGO
Frontier labonsite$350k–$475k
At a glance
Highlights
- Build core systems enabling efficient training of trillion-parameter models.
- Improve numerical foundations to make large-scale training stable and fast.
- Share learnings via open-source libraries and technical reports.
What they offer
- Generous health, dental, and vision benefits
- Unlimited PTO
- Paid parental leave
- Relocation support as needed
Ideal candidate
A collaborative builder who thrives at the intersection of research and systems and cares about stable, efficient large-scale training. You take initiative across teams to ship robust infrastructure that extends human capability.
Requirements
- Bachelor's degree or equivalent experience in computer science, electrical engineering, statistics, machine learning, physics, robotics, or similar
- Understanding of deep learning frameworks and their underlying system architectures
- Thrive in highly collaborative environment with cross-functional partners
- Bias for action with initiative to work across stacks and teams to ship
- Strong engineering skills with performant, maintainable code and debugging in floating-point numerics, low-precision arithmetic, and distributed systems
- visa sponsorship
- We sponsor visas
- hiring process
- Evergreen role reviewed on an ongoing basis; candidates contacted as new opportunities open, may reapply after 6 months
Lab profile
About Thinking Machines Lab
Builds frontier AI that extends human will and judgment through customizable models and interfaces.
What they build
- Inkling frontier models
- Tinker model customization
- Human-AI communication interfaces
Known for
- Frontier model training
- Post-training and reinforcement learning
- Evaluation infrastructure
- GPU supercomputing and reliability