Research Engineer in Automated Machine Learning

Join Preference Model as a Research Engineer specializing in automated ML and RL environments. Help shape the future of self-directed learning by building robust training infrastructures.

In this role, you'll be at the intersection of research and engineering, pushing the boundaries of post-training on large language models. You will train and evaluate models using proprietary RL environments, architect infrastructure, and implement methodologies for RL agents. Your contributions will have a direct impact on data quality and model capabilities.

Key Responsibilities:

• Train and evaluate models on proprietary RL environments

• Architect and optimize RL training infrastructure

• Design and test training environments and evaluation methodologies

• Profile and optimize training runs for maximum throughput

Requirements:

• Experience with end-to-end LLM post-training pipelines

• Proficiency in Python and PyTorch or JAX

• Familiarity with modern RL training frameworks

• Experience building ML infrastructure at scale

Bring your research and engineering skills to Preference Model and drive innovation in ML.
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