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Member of Technical Staff - Machine Learning Capabilities
Summary by AIEngineer.careers
Member of Technical Staff - Machine Learning Capabilities is a Machine Learning Engineer role (part-time). with Preference Model. in SAN FRANCISCO, US. Imported listing (source: emploive.com). Apply on the employer's site (emploive.com).
Imported listing (source: emploive.com) · Apply on emploive.com
SAN FRANCISCO · US
—
Part-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from emploive.com
Preference Model is seeking a Senior Machine Learning Engineer to design and build high-quality reinforcement learning environments for frontier LLMs. This role blends research and engineering, focusing on creating robust reward functions and training infrastructure to advance model capabilities in ML research tasks. The ideal candidate has deep expertise in transformer internals, LLM inference, and systems programming.
Responsibilities
- Design and implement RL environments and reward functions for frontier models
- Develop novel approaches for ML research and engineering tasks
- Conduct experiments and evaluations to validate environment quality
- Deliver work into production training runs
- Collaborate with researchers and engineers to improve the environment building process
Requirements
- 5+ years of experience in machine learning or research, primarily on LLMs and transformers
- Strong ML fundamentals with broad research interests
- Proficiency in Python and systems programming
- Experience with PyTorch or JAX
- Ability to translate research concepts into RLVR problems
Nice to Have
Preference Model
San Francisco · US · 20+ employees
Preference Model builds reinforcement learning (RL) environments that automate machine learning (ML) research and engineering. The company develops infrastructure software to support RL experimentation and partners with frontier AI labs to advance LLM capabilities.
