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Turing is a research accelerator for frontier AI labs, building large-scale datasets and reinforcement learning environments that power post-training for leading AI companies including OpenAI, Anthropic, Google DeepMind, Microsoft, Amazon, and Apple.
As Senior Research Engineer, you will own end-to-end creation of datasets, RL environments, and evaluations for coding agents and software engineering domains. This is a hands-on technical leadership role where you directly influence revenue by mapping to one or more AI lab customers and interfacing with their researchers to understand needs and build data solutions.
Key responsibilities include:
**End-to-End Ownership**: Lead dataset and RL environment creation for coding agents. Ensure all deliverables meet frontier standards for realism, correctness, diversity, and difficulty. Design quality rubrics, automated validation scripts, and human review processes. Build and lead cross-functional teams of software engineers, researchers, QAs, and data annotators from Turing's 4M+ developer network. Interview, onboard, train, and mentor team members.
**Customer Collaboration**: Act as primary technical contact for customer projects, interfacing directly with researchers at frontier AI labs. Understand their coding agent roadmaps and model data needs. Provide regular progress updates, surface insights from model evaluations, and incorporate feedback for continuous improvement.
**Research & Thought Leadership**: Fine-tune models in-house on Turing-generated datasets to validate data quality. Build benchmarks and run evaluations on frontier models to identify strengths and weaknesses on software engineering tasks. Drive sales enablement and industry thought leadership.
**Technical Execution**: Define and manage data pipelines, validation workflows, and review processes. Develop automations, synthetic data generation systems, and internal tools to scale production. Run your project like a startup within Turing, owning both technical architecture and operational execution.
You'll work across multiple environment types: software engineering/coding agents, UI-based computer-use/browser-use agents, and MCP-based function-calling agents for enterprise and consumer applications.
