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Salary: USD 250,000 - 400,000 / annual
Turing accelerates superintelligence by building large-scale datasets, reinforcement learning environments, and frontier research benchmarks that improve AI model capabilities. The company works with leading AI labs and Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to develop agentic AI systems for mission-critical workflows.
As a Staff Research Engineer on the Frontier Data team, you will work at the intersection of research and engineering to investigate high-impact questions that improve real-world AI systems. You will design and run rigorous experiments, develop research-grade prototypes and tooling, and collaborate across Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications.
Key responsibilities include:
1. Conduct Research on Frontier AI Systems: Investigate capabilities, limitations, and training methods of frontier AI systems. Formulate research questions that inform Turing's products and technical strategy. Explore new approaches to synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. Stay current with advances in machine learning and identify opportunities for meaningful technical contribution.
2. Build and Evaluate Research Systems: Develop research-grade datasets, experiments, prototypes, tooling, and evaluation frameworks. Train, test, and evaluate models using modern AI tools. Analyze results carefully and draw evidence-based conclusions. Establish sound practices for experimental rigor, data quality, reproducibility, and interpretation. Iterate quickly from early hypothesis through validated technical insight.
3. Translate Research into Practical Impact: Collaborate closely with cross-functional teams. Translate research findings into improvements for Turing's products and AI capabilities. Help identify which ideas are ready to move from exploration into scalable applications. Communicate technical findings clearly to specialized and cross-functional audiences.
4. Contribute to the Research Community: Share findings through technical reports, publications, open-source work, workshops, and conference participation. Contribute to Turing's research culture through technical discussions, peer review, mentorship, and collaboration. Represent Turing thoughtfully within the broader AI research community.
You will work on RL environments for software engineering agents, UI-based computer-use/browser-use agents, and MCP-based environments for general function-calling agents across enterprise and consumer applications. The role offers high autonomy, rapid iteration, and meaningful commercial impact.
This role is required to be in-office five days per week at one of Turing's offices in San Francisco, Palo Alto, or Seattle.
QUALIFICATIONS:
- PhD or Master's degree in artificial intelligence, machine learning, computer science, or closely related technical field; exceptional equivalent research experience will be considered
- Strong foundation in machine learning with practical experience designing experiments, training or evaluating models, and working with modern AI tooling
- Demonstrated research experience in synthetic or agentic data generation, reinforcement learning or post-training, AI understanding, evaluation, or benchmarks
- Strong programming skills and ability to implement, test, and iterate quickly in a research environment
- Sound judgment around experimental rigor, data quality, reproducibility, and evidence-based decision-making
- Clear written and verbal communication skills, intellectual curiosity, and ability to work effectively across research and engineering teams
