About the role
Turing 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. Main tasks listed: Conduct Research on Frontier AI Systems; Investigate the capabilities, limitations, and training methods of frontier AI systems; Formulate research questions that inform Turing’s products, platforms, and technical strategy; Explore new approaches to synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation.
Experience
PhD 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
Selection process
Apply through the official Turing page (free account required). The listing describes this selection process: AI Interview (~20 mins); Delivery interview (~45 mins).
Eligibility
Not stated on the listing (remote)