Turing · 2 months ago
Frontier Data Lead - RL Gyms
Turing is a leading research accelerator for frontier AI labs based in San Francisco, California. They are seeking a Frontier Data Lead – RL to manage the end-to-end lifecycle of reinforcement learning environment projects, ensuring high-quality delivery tailored to client specifications.
Artificial Intelligence (AI)Generative AIInformation TechnologyMachine LearningSoftware Engineering
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
Qualification
Required
RL & Post-training experience: familiarity with RL fine tuning, verifier/reward design, and/or environment design
Engineering Management experience: have led teams of engineers in the past, including interviewing/hiring them and setting up QA processes
Systems thinking + Database/API design: ability to ‘simulate' the data schema and API interface of a consumer or business application
Hands-on technical capability: willing to write code along with the team you're managing; Python and SQL experience preferred
Operational leadership: Proven ability to manage complex data pipelines, multi-stakeholder delivery, and concurrent high-stakes projects
Cross-functional communicator: ability to communicate clearly with researchers at frontier AI labs, subject matter experts for various domains, and diverse teams
Preferred
Background in Computer Science, Machine Learning, or related technical field preferred
Benefits
Amazing work culture (Super collaborative & supportive work environment; 5 days a week)
Awesome colleagues (Surround yourself with top talent from Meta, Google, LinkedIn etc. as well as people with deep startup experience)
Competitive compensation
Flexible working hours
Company
Turing
Turing advances frontier AI and builds real-world systems for Fortune 500 companies, governments, and the world’s leading AI labs.
H1B Sponsorship
Turing has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (16)
2024 (8)
2023 (7)
2022 (16)
2021 (6)
Funding
Current Stage
Late StageTotal Funding
$270.19MKey Investors
Khazanah NasionalAltaIR CapitalWestBridge Capital
2025-03-06Series E· $111M
2021-12-07Convertible Note· $6.85M
2021-10-04Series D· $87M
Recent News
Foundation Capital
2025-12-31
2025-11-22
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