Member of Technical Staff

ABOUT MERCOR Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.   Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. ABOUT DEEPTUNE Deeptune builds high-fidelity training environments where AI agents learn to complete real work through reinforcement learning. Our environments support areas such as computer use, code generation, and multi-step task completion. In July 2026, Mercor acquired Deeptune. Together, Mercor provides expert human data and Deeptune provides the environments in which agents train. Deeptune is headquartered in New York, and this role joins our remote team in India. Mercor on the acquisition https://www.mercor.com/blog/mercor-to-acquire-deeptune/ | Fortune https://fortune.com/2026/07/09/ai-unicorn-mercor-acquires-deeptune-brendan-foody-investor-a16z-openai-anthropic/ | a16z: Why we're investing in Deeptune https://a16z.com/announcement/investing-in-deeptune/   THE ROLE AI agents need realistic places to practice before they can perform useful work. You will build those environments and the infrastructure that makes them reliable. This is an applied engineering role. You will own production software from an initial specification through implementation, testing, and delivery. The work changes with the needs of AI labs, so you should be comfortable learning unfamiliar domains and moving quickly without sacrificing technical quality.   WHAT YOU'LL DO As a Member of Technical Staff, you may: - Build environments end to end. Create high-fidelity applications that reproduce the behavior and workflows of professional software. - Make environments operable by agents. Build tool APIs, MCP servers, containerized computer-use systems, and the infrastructure that connects an environment to an agent. - Create and calibrate tasks. Design realistic problems, analyze rollouts, tune difficulty, and determine whether failures come from the model, the task, or the environment. - Design realistic data. Build schemas, large corpora, anonymization pipelines, and fast search and loading systems. - Improve shared engineering infrastructure. Build automation, QA systems, deployment tooling, and workflows used across the team. WHAT WE ARE LOOKING FOR - Strong Python skills with enough range across backend, frontend, data, and infrastructure to build a complete application. - Experience owning technically substantial projects, preferably from an early stage through production. - Clear, structured communication. You can make a complex system understandable and answer technical questions directly. - Technical depth. You understand why a system works, how its components interact, and where it can fail. - Good judgment about architecture, tradeoffs, testing, reliability, and scope. - Comfort working with changing requirements, close deadlines, and unfamiliar problem spaces. HOW WE WORK - The India team works remotely with time overlap with New York. - Engineers own outcomes, communicate risks early, and unblock themselves. - Specifications may be incomplete. You are expected to clarify what matters, make sound decisions, and carry work through delivery. - We value practical depth over impressive terminology and working software over unnecessary complexity. COMP - $80,000 - $150,000 (USD) - Mercor Equity - Benefits   INTERVIEW PROCESS We keep the process focused on the two signals most important for this role: communication and technical expertise. - Application review: We review your experience and project work for evidence of relevant engineering depth. - Round 1: Sixty (60) minutes with an engineer, focusing on communication and a technical deep dive. - Choose the technically strongest system you personally helped build. You will walk through the problem, architecture, your contribution, important decisions, tradeoffs, failures, testing, and what you would redesign today. You may use a whiteboard or diagramming tool. - We do not expect experience in one specific domain. We care whether you understand your technical work deeply and can explain it clearly. - Round 2: Hackathon - take-home build expected to take 6 to 8 hours, with a maximum of 8 hours. - You will receive a detailed brief and supporting materials. We assess the functionality of the result, technical decisions, code quality, testing, reliability, scope management, and your understanding of what you built. AI use is allowed. - Both interview rounds are eliminatory. Candidates who pass the hackathon proceed to the final hiring decision. HOW TO PREPARE For Round 1, choose one project that: - You know the technical details in depth. - Shows your personal contribution clearly. - Includes meaningful architecture or implementation decisions. - Gives you examples of tradeoffs, failures, debugging, testing, and lessons learned. Be ready to diagram the system and trace a request or unit of data through it. Clear reasoning and honest acknowledgment of uncertainty are more useful than rehearsed answers.   CONTACT For any questions/information reach out to chirag@deeptune.com/chiragsharma@mercor.com