Staff Research Engineer, Frontier AI Evaluation

As a Staff Research Engineer, you will study the capabilities, limits, and training methods of advanced AI systems. You will combine research and engineering to produce reliable findings and turn validated technical ideas into scalable AI applications.

• Formulate research questions and design experiments that produce evidence-based conclusions.
• Build datasets, prototypes, tools, benchmarks, and evaluation frameworks for complex, multi-step workflows.
• Train, test, and evaluate models with modern machine learning tools.
• Explore reinforcement learning, post-training, synthetic and agentic data generation, model understanding, AI evaluation, and tool-using systems.
• Help develop environments for coding agents, computer-use and browser-use agents, and function-calling systems.
• Analyze experimental results with attention to data quality, rigor, and reproducibility.
• Work with research, engineering, product, and operations stakeholders.
• Share findings through technical reports or other suitable channels, and contribute to technical discussions, peer review, mentoring, and research collaboration.

This is a part-time contractor role open worldwide. The role requires at least 20 hours per week and professional fluency in English.

• Pay: Not provided in the role details.
• Education: A PhD or master's degree in artificial intelligence, machine learning, computer science, or a closely related technical field, or equivalent research experience.
• Experience: At least 7 years of professional experience, including significant research engineering work in machine learning or frontier AI systems.
• Practical background designing experiments, training or evaluating models, or developing AI systems.
• Strong Python programming skills and experience with modern AI and machine learning frameworks.
• Sound judgment about experimental rigor and reproducibility.
• Clear communication, independent execution, cross-functional collaboration, and technical mentoring experience.
• Useful research background in synthetic or agentic data generation, reinforcement learning, post-training, model understanding, AI evaluation, benchmarks, agents, or tool-using systems.
• Helpful experience includes coding-agent environments, user-interface or browser-use environments, function-calling systems, technical publications, open-source research, or major machine learning conferences.

Apply on OpenTrain with your resume, then complete the application on the hiring site.

AI training is the human work behind modern AI systems. People create and review datasets, test model behavior, and provide feedback so these systems become more useful and reliable; advanced technical experience matters for research and evaluation work.

OpenTrain helps people find and build careers in AI training and data labeling by offering projects across the industry, profiles for showing relevant experience, and applications through one account.