Member of Technical Staff - Research & Post-training

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

• Train and evaluate models on proprietary RL environments to validate data quality and surface gaps in task coverage
• Architect and optimize RL training infrastructure using frameworks like Verl or OpenRLHF
• Design, implement, and test training environments, evaluations, and methodologies for RL agents
• Profile and optimize training runs end-to-end to maximize experiment throughput

Requirements

• Experience running end-to-end LLM post-training pipelines
• Proficiency in Python and PyTorch or JAX
• Experience with at least one modern RL training framework
• Experience building and operating ML infrastructure at scale

Preferred Qualifications

• Experience evaluating model outputs and building reward or evaluation signals
• Ability to translate research papers into running code
• Strong systems design and communication skills
• Ability to balance research exploration with engineering rigor

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