Member of Technical Staff - Machine Learning Capabilities, New Graduates
Preference Model · San Francisco
Infrastructureonsiteentry-level$165k–$200k
At a glance
Highlights
- Design RL environments that teach frontier models ML research tasks.
- Own environments end-to-end from idea to production training runs.
- Build the data layer powering frontier LLM capabilities.
What they offer
- Competitive cash and equity compensation (>90th percentile)
- Health, vision and dental benefits
- 401K match
- Lunch provided everyday onsite
- Weekly snack orders
- Visa sponsorship & relocation support available
Ideal candidate
Recent PhD graduate with research publications who reads deeply across ML and wants full ownership building RL environments that advance frontier models.
Requirements
- Strong ML fundamentals and broad research interests
- Expert knowledge in an active DL/ML research area with publications or public code
- PhD with research experience strongly preferred
- Deep understanding of transformer internals
- Proficiency in Python, Numpy and systems programming, ideally PyTorch or JAX
- Takes ownership and drives solutions end-to-end
- Passion for staying current with evolving ML infrastructure
- Ability to meet throughput expectations and respond quickly to feedback
- visa sponsorship
- Visa sponsorship available
Lab profile
About Preference Model
Superintelligence data research company building RL environments for capable, better-aligned AI.
What they build
- RL environments for superintelligence training
Known for
- Reinforcement learning environments
- Reward signals for capability and alignment
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