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T
AI Systems Engineer
Transluce
San FranciscoOn-site1y ago
- Employment
- Full-time
About the role
- Set overall code culture and tooling for a fast-growing org
- Help to solve our core technical challenges across verticals. Examples include:
- Docent:
- High-concurrency container-based evals with quick ability to iterate on interventions to agentic trajectories
- Deterministic sandbox execution of code that can efficiently restore state from checkpoints
- Interpretability:
- Inference stacks that are as performant as vLLM but flexible enough to allow complex model introspection and intervention, steering, configurable sampling, etc., and that can scale to 400B+ parameter models
- Behavior elicitation:
- Distributed RL training and roll-outs allowing thousands of concurrent rollouts across machines
- Build great internal tools to speed up the team
- Docent:
- Help tone-set in the organization around best practices for building and path-set on what infra we should build
- Help other team members think through infra challenges
- Exceptional programmer fluent in Python
- Bare metal optimization: know GPUs, other accelerators in and out (low-level performance + optimization + parallel programming)
- Experience engineering at scale (distributed systems, reliability, architecture design)
- Leader on global code quality and health (designing good primitives, managing complexity and scale)
- Bonus: can set up LLM pipelines, e.g. multiple specialized LLMs interacting with each other in a performant and reliable way
- Bonus: experience with open-source community management
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