Investigate and develop systems to enhance frontier AI capabilities. About Turing: Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems.
About the role
Investigate and develop systems to enhance frontier AI capabilities. About Turing:
Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L
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.
Our work includes:
Software engineering environments for coding agents
UI environments for computer-use and browser-use agents
MCP-based environments for function-calling agents across enterprise and consumer applications
We 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 Do …
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