Applied Research Engineer

Key responsibilities: Build and maintain important open-source reinforcement learning, environment, evaluation, and agent systems Develop researcher-facing features in the training platform in collaboration with engineering and design teams Create APIs, examples, and reference implementations that expose useful abstractions for external contributors

Required qualifications: Relevant experience in open-source ML or developer-tool systems, research engineering, or technical product work Hands-on experience with model-training, post-training, agent, evaluation, or related experimental loops Strong experimental judgment with the ability to analyze baselines and adapt based on evidence Proficiency in Python and capability to build artifacts for inspection and extension by other researchers Comfort with ambiguous problems and effective communication with partners and teammates during resolution