SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 250,000 - 350,000 / annual
Turing accelerates superintelligence by building large-scale datasets and reinforcement learning environments that power post-training for frontier AI labs and enterprises. The company works across synthetic data generation, agentic AI systems, and enterprise deployment, closing the loop between research and real-world application.
As a Senior Research Engineer, you will work at the intersection of research and engineering to investigate high-impact questions that improve frontier 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, and conference participation. Contribute to Turing's research culture through technical discussions, peer review, and mentorship. Represent Turing within the broader AI research community.
The role focuses on RL environments for evaluating and improving models on complex workflows across 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.
Requirements:
- 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
This role requires in-office presence five days a week at Turing's offices in San Francisco, Palo Alto, or Seattle.
