Frontier Data Lead, RL Gyms - US at Turing in San Francisco, CA

About Turing Based in San Francisco, California, 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. Recognized by Forbes, The Information, and Fast Company among the world’s top innovators, Turing’s leadership team includes AI technologists from Meta, Google, Microsoft, Apple, Amazon, McKinsey, Bain, Stanford, Caltech, and MIT. Learn more at www.turing.com About Turing Based in San Francisco, California, 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. Recognized by Forbes, The Information, and Fast Company among the world's top innovators, Turing's leadership team includes AI technologists from Meta, Google, Microsoft, Apple, Amazon, McKinsey, Bain, Stanford, Caltech, and MIT. Learn more at www.turing.com About Turing Turing builds large-scale datasets and reinforcement learning (RL) environments that power post-training for the world's leading AI labs and enterprises. 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, and Customer Experience. The environments vary depending on the model capability being evaluated or improved. A few examples of environment types include: 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 The Role We are looking for a Staff Research Engineer, RL Gyms to design, build, and iterate on the RL environments that frontier AI labs use to evaluate and improve their models. This is a hands-on, deeply technical IC role — you will own the architecture and implementation of complex, realistic environments that simulate real-world software systems and business workflows. You will work directly with researchers at leading AI labs to translate their post-training objectives into environment specifications, then build the infrastructure to make those environments run at scale. You will set technical direction for environment design patterns, reward and verifier systems, and data generation pipelines — influencing how multiple project teams approach these problems across Turing. What You'll Do Environment Architecture & Implementation: Design and build RL environments that simulate real-world applications — defining database schemas, API interfaces, seed data, task distributions, and verifier logic. Write production code daily alongside your project teams. Reward & Verifier Design: Architect reward functions and verification systems that accurately measure agent performance on complex, multi-step workflows. Ensure reward signals are well-calibrated, resistant to reward hacking, and aligned with the capabilities the client is training for. Technical Direction: Set design patterns and best practices for environment construction across multiple concurrent projects. Establish reusable frameworks, review architectures proposed by other engineers, and raise the technical bar for environment quality, realism, and difficulty. Data Quality & Rigor: Define and enforce quality standards for environments and the data they produce (agent trajectories, reward scores, task distributions). Build automated validation, difficulty calibration, and diversity analysis tooling. Research Collaboration: Work directly with researchers at frontier AI labs to understand their post-training goals, translate those into environment requirements, and iterate based on experimental results. Serve as the primary technical counterpart in these conversations. Evaluation & Experimentation: Run in-house RL fine-tuning experiments and eval benchmarks to measure model performance lifts on your environments. Use experimental results to refine environment design and demonstrate proof of value to clients. Mentorship & Leverage: Raise the capabilities of engineers on your project teams through code review, architecture guidance, and pair programming — without formal management responsibility. Who We're Looking For Deep RL & post-training expertise: Hands-on experience with RL fine-tuning, reward/verifier design, environment design, or RLHF pipelines. You understand the training loop end-to-end, not just the environment layer. Strong software engineering fundamentals: You write clean, reliable, production-grade code. Python and SQL proficiency required. Experience designing database schemas and API interfaces for complex systems. Systems thinking: Ability to look at a real-world application (e.g., an investment banking workflow, a developer tool, a CRM) and decompose it into a faithful simulated environment with realistic state, transitions, and edge cases. Experimentation rigor: Comfort running training experiments, interpreting reward curves, diagnosing environment issues from model behavior, and iterating rapidly based on results. Technical influence without authority: Track record of raising engineering quality across teams through design review, best practices, and mentorship — not through a management title. Strong communicator with researchers: Ability to engage deeply with ML researchers at frontier labs, understand their objectives, and translate between research goals and engineering implementation. Background in Computer Science, Machine Learning, or related technical field required. Advanced degree (MS/PhD) in a relevant area preferred. Why Turing Work directly with the world's leading AI labs and enterprises at the cutting edge of RL environment design and post-training. Real impact: your environments will be used to evaluate and train frontier models on GDP-moving tasks across real-world domains. Talent-dense team where you'll find high autonomy, rapid iteration, and a steep learning curve. Compensation $250,000 to $350,000 OTE + Equity Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile, and favor action because momentum is the foundation of perfection. We are AI forward: We help our clients build the future of AI and implement it in our own roles and workflow to amplify productivity. Advantages of Joining Turing 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 Don't meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive, and authentic workplace and celebrate authenticity, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here. Values: We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are Al forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing: 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 Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here.