--- title: 'Member of Technical Staff - India at Deeptune' canonical: 'https://feeny.ai/job/member-of-technical-staff-india-deeptune-india-0g6wrdqgfs4d' type: 'job' last_seen: '2026-09-01' --- # Member of Technical Staff - India at Deeptune - **Company:** Deeptune - **Location:** India - **Employment:** full-time - **Work type:** remote - **Posted:** 2026-01-06 - **Last confirmed live:** 2026-09-01 - **Apply:** https://jobs.ashbyhq.com/deeptune/c7b5eebb-4e36-4c02-9888-7ca74d4a726c ## Job description ## 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 ## About Deeptune ## Core Business - **Primary industry**: Artificial Intelligence / Research Services - **Target customers**: B2B – frontier AI research labs (e.g., leading model developers) - **Mission or purpose**: To accelerate AI agent capabilities by providing realistic, scalable training environments that mimic real-world software. ## Products & Services - **Training Gyms (Simulation Environments)**: SaaS / API – Hundreds of pre-built gyms that emulate popular software (Slack, Salesforce, etc.) – each gym comes with problems, datasets, and infrastructure. Labs integrate these in “a few lines of code” to train and evaluate AI agents. ## Market Standing - **Valuation/Market Cap**: Not disclosed - **Key Metrics**: Total funding raised – **$46.1M** (Series A of $43M led by Andreessen Horowitz, plus earlier rounds); Annual Recurring Revenue – **7-figure ARR** achieved within the first six months of operation. - **Notable Investors/Partners**: Andreessen Horowitz (lead of Series A), Inspired Capital, Abstract, Yash Patil, Noam Brown, and 11+ others. - **Growth Signals**: Headcount grew **283% YoY** to 17 employees; raised a $43M Series A in mid-2025; expanded to a new office in Union Square, NYC; works with leading AI labs; 4 active job postings (as of July 2025). ## Competitive Advantages - **Specialized focus** on training infrastructure for AI agents, a niche that is critical as labs move from language models to agentic systems. - **First-mover advantage** in building realistic, software-mimicking gyms at scale (hundreds of gyms already built). - **Traction with top labs** – 7-figure ARR in under 6 months signals strong product-market fit. - **Tight integration** – gyms are designed to be dropped in with “a few lines of code,” lowering adoption friction. ## Strategic Focus - Scale the number and variety of training gyms to cover more software categories. - Deepen partnerships with frontier research labs to co-create gyms for emerging agent use cases. - Grow the engineering and operations team (open roles: Member of Technical Staff, Domain Experts in Accounting/Finance/Sales, Strategic Projects Lead). ## Why Work Here - **Culture**: Values craft mastery, comfort with ambiguity, and diverse perspectives. Described as a place for “engineers and builders.” - **Work environment**: **Fully in-office** – 5 days a week at the Union Square, NYC office. Strong emphasis on in-person collaboration. - **Growth trajectory**: Early-stage (Series A) with proven revenue traction and backing from top-tier investors (a16z). Opportunity to shape the product and company from an early stage. - **Team**: Small, high-caliber team (17 people) – alumni from companies like Glean, Uber, Retool, Hebbia, Scale AI, Anthropic. ## Sources 1. [deeptune.ai](http://deeptune.ai/) 2. [linkedin.com](https://www.linkedin.com/company/deeptuneai) 3. [cbinsights.com](https://www.cbinsights.com/company/deeptune) 4. [builtinnyc.com](https://www.builtinnyc.com/company/deeptune) 5. [jobs.ashbyhq.com](https://jobs.ashbyhq.com/deeptune)