Research Scientist, Safety Post Training
Scale AI · San Francisco, CA; New York, NY · Research · listed May 18, 2026
The shape of it
Seniority
Not stated
Where
Not stated
Stated pay
$216,000 – $270,000 USD
Requirements listed
5
Length
903 words
In the posting’s own words
As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities.
What it asks for · 5
- Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches.
- A track record of published research in machine learning, particularly in generative AI.
- At least three years of experience addressing sophisticated ML problems, whether in a research setting or in product development.
- Experience with mechanistic interpretability, probing, or other techniques for understanding model internals.
- Familiarity with red-teaming or adversarial evaluation of post-trained models.
Also a plus
- Experience with mechanistic interpretability, probing, or other techniques for understanding model internals.
- Familiarity with red-teaming or adversarial evaluation of post-trained models.
- Experience studying failure modes introduced or masked by post-training, such as reward hacking, sycophancy, or alignment faking.
Tools and skills named
Models & research
- Evaluations2×
- Machine learning2×
- Reinforcement learning
Ways of working
- Cross-functional
Words the posting leans on
- research7×
- post-training6×
- evaluation5×
- models5×
- experience4×
- safety4×
- capabilities3×
- frontier3×
- industry3×
- interpretability3×
- policymakers3×
- researchers3×
- risk3×
- techniques3×
- alignment2×
- collaborate2×
Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.
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