Research Engineer - Oversight Foundations
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Before you apply
Salary$250k – $500k
LocationSan Francisco, United States
Work modeon-site
Typefull-time
SenioritySenior
DepartmentEngineering & Research
Company size51–200 people
PostedJun 10, 2026 · 4mo ago
Verified live1d ago
May no longer be actively hiring
Posted by the company on Jun 10, 202664% of this company's open roles have been listed for 90+ days
At a glanceSummarised by Seekless from the posting.
Experience with fine-tuning language models, designing new architectures, and creating evaluations
Reliable results: good experimental design, epistemic self-awareness and transparency
Generativeness: coming up with original, productive ideas for unblocking progress
Curiosity: a desire to understand ML systems and how they work
Strong programming ability, including navigating trade-offs between prototyping speed and maintainability
Strong communication skills, low ego, openness to giving and receiving feedback
Salary range: $250,000 - $500,000/year + benefits
About the company
Description: Transluce is a non-profit research lab building tools for scalable, end-to-end oversight of AI systems. We build world-class, AI-backed analysis tools and use these to set industry standards for evaluation. Our tools are integrated with core agent benchmarks like SWE-bench, while our evaluations are directly underpinning regulation, including our role as EU AI Office’s main evaluation developer for harmful manipulation risks.
About the role
About the role: We are looking for strong scientists and engineers to help advance our vision ofoversight foundation models: AI systems that formalize, test, and answer questions about the behavior of other AI systems. As part of our highly collaborative team, you will learn and grow quickly, creating technology at the frontier of AI research and with high direct impact.
Responsibilities
Core responsibility: Help us develop and train scalable oversight assistants that can predict and detect unexpected and subtle behaviors in AI systems. This includes:
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Creating diverse evaluations that range in difficulty. This involves finding naturally occurring interesting and undesirable behaviors exhibited by open-source models.
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Developing novel architectures and objectives for training oversight assistants.
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Scaling up the training and inference pipelines to support up to 1T-scale models.
Qualities of a strong candidate:
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Experience with fine-tuning language models, designing new architectures, and creating evaluations.
•
Reliable results: good experimental design, epistemic self-awareness and transparency
•
Generativeness: coming up with original, productive ideas for unblocking progress
•
Curiosity: a desire to understand ML systems and how they work
•
Strong programming ability, including navigating trade-offs between prototyping speed and maintainability
•
Strong communication skills, low ego, openness to giving and receiving feedback
We are located in San Francisco and enthusiastic to work together in-person. We are open to sponsoring international visas.