Join Preference Model as a Research Engineer to design and build RL environments for advancing machine learning capabilities.
Posted by employer 3 days ago
First seen on Joblaze 2 days ago
Last verified on the company career page 16 hours ago
What you'll build
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Requirements
Not disclosed in this posting: compensation, work arrangement.
Benefits
Joblaze summary
In this role, the engineer will design and implement reinforcement learning environments that enhance the capabilities of frontier machine learning models. Candidates should have over five years of experience in machine learning, particularly with large language models, and be proficient in Python and frameworks like PyTorch or JAX. This position is ideal for seasoned professionals who are problem solvers and can take ownership of their projects, contributing to a small, high-ownership team focused on advancing AI training methodologies.
Joblaze insights
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From the original posting
We’re hiring experienced Machine Learning Engineers to design and build reinforcement learning environments to safely advance model capabilities in machine learning research and engineering. Specifically, you'll be teaching frontier models to do the work of an ML engineer or researcher 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.
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
5+ years of experience working in machine learning or research, primarily on LLMs and transformer models
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
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
Competitive cash and equity compensation (>90th percentile)
Health, vision, dental, benefits
401K match
Lunch provided everyday onsite
Weekly snack orders
Visa sponsorship & relocation support available
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