AI Systems Engineer

Salary range:

$350,000 - $600,000/year + benefits

Description:

Transluce is a fast-moving research lab building the public tech stack for understanding and debugging AI systems. We build world-class, AI-backed analysis tools and use these to set industry standards for evaluation. We are a non-profit with a mission to steer the development of AI for the public good.

About the role:

We are looking for an exceptional AI systems engineer to lead the design and development of our core ML stack , building systems that can scale to thousands of GPUs and performantly query trillion-token databases.

As an early member of a highly collaborative team, you will be free to innovate and move fast, building high-impact systems from the ground up. As part of a mission-focused non-profit, your work will have high direct impact (e.g. used by governments to inform AI policy) and cross-organisational reach (open-source tools the entire community can build on).

Core responsibilities:

• 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
• 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

Qualities of a strong candidate:

• 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

We are located in San Francisco and enthusiastic to work together in-person. We are open to sponsoring international visas.