Preference Model is building the next generation of training data to power the future of AI. Backed by a16z and South Park Commons.
About the role
We’re hiring new graduate 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.
What they're looking for
- 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
- Expert knowledge in an active DL/ML research area, with publications or public code to show for it
- Research experience (PhD, MS) is a strongly preferred
- Deep understanding of transformer internals
- Proficiency in Python, Numpy, and systems programming, ideally PyTorch or JAX
- Smart problem solvers who take ownership and drives solutions end-to-end
More about this role
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.
We’re hiring new graduate 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...
Browse similar: AI jobs · AI startup jobs · Startup jobs · San Francisco Bay Area