Staff Research Engineer - Frontier AI, RL & Evaluation

Staff Research EngineerCareerflow Human Data Labs partners with AI companies to bring real-world professional expertise into their products.We builds large-scale datasets and reinforcement learning environments that power post-training for leading AI labs and enterprises. Our environments evaluate and improve AI models on complex, long-range, multi-step workflows across high-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, and Customer Experience.Our work includes:Software engineering environments for coding agentsUI environments for computer-use and browser-use agentsMCP-based environments for function-calling agents across enterprise and consumer applicationsWe are looking for Staff Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training.This role sits at the intersection of research and engineering. You will investigate high-impact questions, design rigorous experiments, build research-grade prototypes and tooling, and collaborate with Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications.You will contribute to areas including synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation.What You'll DoConduct research on frontier AI systemsBuild and evaluate research systemsTranslate research into practical impactContribute to the research communityWhat We're Looking ForPhD or Master's degree in Artificial Intelligence, Machine Learning, Computer Science, or a closely related technical field. Exceptional equivalent research experience will also be considered.Minimum 7+ years of professional experience with significant research engineering experience working on machine learning or frontier AI systems.Strong foundations in machine learning and practical experience designing experiments, training models, evaluating models, or developing AI systems.Demonstrated research experience in one or more of the following areas: synthetic or agentic data generation, reinforcement learning or post-training, model understanding, AI evaluation, benchmarks, AI agents or tool-using systems.Strong programming skills, particularly in Python, with the ability to implement, test, and iterate quickly in a research environment.Experience with modern AI and machine learning frameworks and tooling.Strong scientific judgment around experimental rigor, data quality, reproducibility, and evidence-based decision-making.Excellent written and verbal communication skills.Ability to work independently and collaborate effectively across research and engineering teams.Experience mentoring engineers or researchers and providing technical leadership.Location: USA, Country Specific Guidelines and Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Pakistan, Indonesia, Nigeria, Turkey, Vietnam