Connectionism: Research Blog by Thinking Machines Lab. Backed by a16z, Accel and GV.
About the role
This role is responsible for building and strengthening the engineering foundations that our post-training research teams depend on. You'll embed within a research team, and build or improve the systems required for the team to succeed. Our research teams are small, and the role carries a corresponding degree of autonomy and responsibility. Embed within a research team to build, harden, and improve the systems and infrastructure required for the team to succeed.
What they're looking for
- Bachelor’s degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding
- Experience leading projects end to end, working in large fast-moving codebases, and writing code others have depended and built on
- Strong proficiency in Python and strong engineering fundamentals, with experience debugging systems that fail intermittently and at scale
- Clarity in communication, an ability to explain complex technical concepts in writing
- Strong autonomous drive to progress towards the team’s goals with an ownership mindset
- Preferred qualifications — we encourage you to apply even if you don’t meet all preferred qualifications, but preferably some:
More about this role
The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it.
This role is responsible for building and strengthening the engineering foundations that our post-training research teams depend on. You'll embed within a research team, and build or improve the systems required for the team to succeed. Our research teams are small, and the role carries a corresponding degree of autonomy and responsibility.
Embed within a research team to build, harden, and improve the systems and infrastructure required for the team to succeed.
Design, build, and operate infrastructure research teams depend on, including RL training systems, sandboxing, data pipelines, and agent scaffolding.
Bachelor’s degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding.
Experience leading projects end to end, working in large...
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