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ML Research Engineer
TransluceSan Francisco, United Statesfull_timeVerifiedPosted 16 Jan 2025
š° $340,000/yr($250,000/yr ā $340,000/yr)
About the role
Salary range: $250,000 - $340,000/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 strong ML engineers to accelerate progress on our core LLM-based AI technology, spanning RL, interpretability, and AI agents. As an early member of a highly collaborative team, you will learn and grow quickly, creating technology at the frontier of AI research and with high direct impact.
Core responsibility: Drive results on one of our core research threads; proactively identify and execute on tactical paths forward within a broader team strategy. This includes:
Qualities of a strong candidate:
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 strong ML engineers to accelerate progress on our core LLM-based AI technology, spanning RL, interpretability, and AI agents. As an early member of a highly collaborative team, you will learn and grow quickly, creating technology at the frontier of AI research and with high direct impact.
Core responsibility: Drive results on one of our core research threads; proactively identify and execute on tactical paths forward within a broader team strategy. This includes:
- Prototyping to reach signs of life on an initial idea
- Navigating the design space of system architecture and other hyperparameters
- Designing and implementing efficient and reliable systems (training and inference pipelines)
- For more senior candidates: direction setting on code code architecture, planning and leading projects
Qualities of a strong candidate:
- Reliable and trustworthy results: meticulous, good experimental design, epistemic self-awareness and transparency
- Prioritization: be scrappy while balancing appropriately with meticulousness
- Keep low-level planning connected to high-level goals
- Generative: come up with original, productive ideas for unblocking progress
- Deep domain knowledge in some area of ML research, such as interpretability, RL, basic systems performance / GPUs
- Strong programming ability, including navigating trade-offs between prototyping speed and maintainability
- Strong communication skills, low ego, openness to giving and receiving feedback
- High self-bar for final results
- Ability to learn quickly from teammates and mentors
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