Member of Technical Staff - Machine Learning Capabilities

Preference Model; San Francisco (CA); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Competitive cash and equity compensation

Health, vision, and dental benefits

401K match

Lunch provided everyday onsite

Visa sponsorship & relocation support

Job summary

Preference Model in San Francisco is seeking experienced Machine Learning Engineers to design and build reinforcement learning environments aimed at advancing model capabilities. The role blends research and engineering, requiring ownership of environment design and implementation.

Successful candidates will have strong ML fundamentals, proficiency in Python, and experience with either PyTorch or JAX. We offer competitive compensation, ownership in a fast-paced environment, and various employee benefits including health coverage and 401K matching.

Qualifications

• Creative in translating research into practical RLVR problems.
• Expert knowledge in deep learning or machine learning research.
• Experience with modern LLMs and inference libraries.

Responsibilities

• Design and build RL environments and reward functions.
• Collaborate with others to improve environment building processes.
• Conduct experiments and deliver production-ready environments.

Skills

Strong ML fundamentals

Proficiency in Python

Systems programming

Experience with PyTorch or JAX

Problem-solving skills

Current knowledge of ML infrastructure

Education

PhD or MS in relevant field

Tools

CUDA

Triton

Pallas

Job description

About Us

Preference Model is building automated ML research engineering.

Existing frontier models are brittle when applied to real-world ML tasks. The present bottleneck is the lack of high-quality RL training environments. Our first step is to build RL environments that reflect real-world complexity, with diverse tasks and robust reward functions.

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.

About the Role

We’re hiring Machine Learning Engineers to design and build reinforcement learning environments to safely advance model capabilities specifically on machine learning research and engineering tasks to do the work of an MLE at a frontier lab.

This role blends research and engineering. It will require you to stay up to date with the latest research, develop novel approaches, and realize them in code. You will have full ownership and autonomy of the environments you build. Your work will include designing and implementing RL environments, conducting experiments and evaluations, delivering your work into production training runs, and collaborating with other researchers and engineers.

You will join our Capabilities org, a small, high-ownership team and contribute directly to the data layer that powers frontier LLM capability.

Note: This role is only for experienced ML Engineers. We have a separate opening for New Grads.

What You Will Do:

• Design and build RL environments and reward functions 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

What We are Looking For (Qualifications):

• You have strong ML fundamentals and broad research interests. You read many papers or tutorials, understand topics deeply and have the creativity to translate them into RLVR problems
• Proficiency in Python and systems programming and at least one of PyTorch or JAX
• Problem solvers who take ownership and drives solutions end-to-end
• Passion for staying current with the rapidly evolving ML infrastructure landscape
• Ability to meet throughput expectations and respond quickly to feedback

You may be a good fit if you also:

• Have expert knowledge in an active DL/ML research area, with publications or public code to show for it. Research experience (PhD, MS) is a big plus
• Have deep understanding of transformer internals, training/inference of modern LLMs, experience with inference libraries (vLLM, SGLang, etc)
• Have strong expertise in kernel development (CUDA, Triton, Pallas)
• Have built complex interactive RL environments

What We Offer:

• Competitive cash and equity compensation (>90th percentile)
• Ownership and autonomy in a fast moving startup environment
• Opportunity to work with top machine learning engineers
• Health, vision, dental, benefits
• 401K match
• Lunch provided everyday onsite
• Weekly snack orders
• Visa sponsorship & relocation support available

We value diverse perspectives and experiences. If you're excited about this role but don't check every box, we still encourage you to apply.