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Posted 10 hours ago
Member of Technical Staff - Machine Learning Capabilities
Preference ModelMember of Technical Staff - Machine Learning Capabilities
Perks & benefits
Health InsuranceVisaRelocation AllowanceCommissionPaid LeaveMedical Insurance
Requirements
Strong ML fundamentals, Proficiency in Python, Systems programming skills, PyTorch or JAX experience
Skills
PythonPyTorchJaxReinforcement Learning
About the role
About the Company
Preference Model is building automated ML research engineering. Our founding team has previous experience on Anthropic’s data team building data infrastructure and datasets behind Claude. We are partnering with leading AI labs to push AI closer to achieving its transformative potential.
Responsibilities
- Design and build RL environments and reward schemes that produce clean, learnable signals for frontier models on ML research and engineering tasks
- Build deep expertise across the frontier of ML research, training, and inference infrastructure
- Collaborate with others to brainstorm and create new ideas and tools to improve the environment building process
Requirements
- Strong ML fundamentals and broad research interests
- Proficiency in Python and systems programming
- Experience with PyTorch or JAX
- Ability to translate research papers into RLVR problems
- Smart problem solver with end-to-end ownership
Preferred Qualifications
- PhD or MS research experience
- Expert knowledge in an active DL/ML research area with publications or public code
- Deep understanding of transformer internals
- Expertise in kernel development (CUDA, Triton, Pallas)
- Experience with RL environments or ML infrastructure open-source contributions
- Experience with cloud platforms (AWS, GCP, Azure) or infrastructure-as-code
Benefits
- Competitive cash and equity compensation
- Ownership and autonomy in a fast moving startup environment
- Health, vision, and dental insurance
- 401K match
- Daily onsite lunch and weekly snacks
- Visa sponsorship and relocation support available
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Get started — it's freeMember of Technical Staff - Machine Learning Capabilities
Preference Model · San Francisco
