Machine Learning Researcher

Job Summary

Focused on reinforcement learning and agentic systems, the full-time Machine Learning Researcher will design and evaluate datasets, tasks, and environments to benchmark advanced AI systems while working remotely.

Key responsibilities

• Design and build datasets, tasks, and environments for benchmarking agentic systems and multi-step model behavior
• Develop frameworks for evaluating the quality of real-world data, including quality scorecards and evaluation methods
• Benchmark model behavior in RL and agentic settings, connecting model failures to dataset or task design gaps

Required qualifications

• PhD or equivalent Master's Degree + 4+ years of industry experience in machine learning or related quantitative fields
• Strong understanding of AI model training pipelines and evaluation methodologies
• Experience with large, unstructured datasets used for training or evaluating ML systems
• Experience in reinforcement learning, sequential decision-making, or agentic systems
• Proven ability to design tasks, benchmarks, and evaluation frameworks for real-world model behavior