Frontier Data Lead - RL Gyms

Turing•San Francisco, CA

10d•Remote

About The Position

Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises looking to deploy advanced AI systems. Turing accelerates frontier research with high-quality data, specialized talent, and training pipelines that advance thinking, reasoning, coding, multimodality, and STEM. For enterprises, Turing builds proprietary intelligence systems that integrate AI into mission-critical workflows, unlock transformative outcomes, and drive lasting competitive advantage. We create RL environments to evaluate and improve our customers' models on complex, long-range, multi-step workflows across high-GDP-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, Customer Experience. The environments vary depending on the model capability being evaluated / improved, a few examples of environment types are listed here: Environments for Software Engineering / coding agents, UI-Environments for Computer-Use/Browser-Use agents, MCP-based Environments for general function-calling agents across various enterprise and consumer applications.

Requirements

Familiarity with RL fine tuning, verifier/reward design, and/or environment design.
Have led teams of engineers in the past, including interviewing/hiring them and setting up QA processes.
Ability to ‘simulate’ the data schema and API interface of a consumer or business application.
Willing to write code along with the team you’re managing; Python and SQL experience preferred.
Proven ability to manage complex data pipelines, multi-stakeholder delivery, and concurrent high-stakes projects.
Ability to communicate clearly with researchers at frontier AI labs, subject matter experts for various domains, and diverse teams.
Background in Computer Science, Machine Learning, or related technical field preferred.

Responsibilities

Lead RL Environment projects end-to-end for one or more clients, ensuring the environment you and your team create matches the client’s spec, surpasses quality expectations, and is delivered on time.
Ensure the RL environments you produce, the data that goes into those environments, and the the data generated from them (e.g. agent trajectories and reward scores) meet frontier standards for realism, difficulty, diversity.
Work with your Ops counterparts to build the team of full-stack engineers, back-end engineers, domain experts, QAs, data creators, reviewers, and others you’ll need to deliver the environment on time. You’ll interview, hire, onboard, train, retain talent for your team.
Set the process that each of the above team members follows to generate environment code, database schemas, seed data, tasks, and verifiers; set up quality rubrics, automated validation scripts, and human-in-the-loop review processes for every aspect of the environment and data for the environment.
Own customer relationships for your RL Environment project(s), and act as the primary point of contact for leading AI labs, providing regular updates, asking for feedback, and identifying opportunities to grow project scope and revenue.
Participate in client solutioning conversations alongside our sales teammates; understand the needs of researchers at AI labs, translate those needs into environment goals.
Demonstrate proof of value for your environments by running inhouse RL fine tuning experiments to measure model performance lifts on agent trajectories; or by producing eval reports of frontier models on your environment and tasks.