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Salary: USD 250,000 - 350,000 / annual
Turing accelerates superintelligence by working with frontier AI labs and enterprises to generate high-quality datasets, reinforcement learning environments, and research benchmarks. The company operates on both sides of the AI development lifecycle: generating data for frontier model training and deploying agentic AI systems in enterprise workflows across finance, life sciences, healthcare, retail, automotive, and CPG.
As a Senior Research Engineer on the Frontier Data team, you will work at the intersection of research and engineering to advance understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training. You will investigate high-impact research questions, 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 ML advances 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 hypothesis through validated technical insight.
3. Translate Research into Practical Impact: Collaborate with Research, Engineering, Product, and Operations teams. Translate research findings into improvements for Turing's products and AI capabilities. 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, or 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.
The role focuses on RL environments for evaluating and improving models on complex, long-range, multi-step workflows across high-GDP-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, and Customer Experience. Environment types include software engineering/coding agents, UI-environments for computer-use/browser-use agents, and MCP-based environments for general function-calling agents.
This is a five-days-per-week in-office role based in San Francisco, Palo Alto, or Seattle.
REQUIREMENTS:
- PhD or Master's degree in artificial intelligence, machine learning, computer science, or closely related technical field; exceptional equivalent research experience 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
