Robotics Project Lead – Data Collection

US Remote – Near SF or New Jersey Preferred (Up to 20% travel as required - SFO, EWR, IGI) Who we are: Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are the AI technology solutions provider-of-choice to 4 out of 5 of the world’s biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine. By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of subject matter experts, and a high-security infrastructure, we’re helping usher in the promise of clean and optimized digital data to all industries. Innodata offers a powerful combination of both digital data solutions and easy-to-use, high-quality platforms. Our global workforce includes over 3,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany. We’re poised for a period of explosive growth over the next few years. Position Summary: Innodata’s Robotics & Physical AI business is at an inflection point, and our data collection initiatives are a core growth driver. As a Robotics Project Lead for Data Collection, you will fully own some of our most visible and high‑impact robotics data programs, making decisions that directly influence data quality, operational efficiency, revenue, and margins. This is a demanding, entrepreneurial role: you’ll wear many hats across solution design, operations, analytics, and cross‑functional coordination, and you should be excited about getting into the weeds to unlock major customer and model wins. Responsibilities: Serve as the end‑to‑end owner for high‑impact robotics data collection projects, from initial scoping through launch, iteration, and scale. Understand customer and internal model requirements and translate them into capture specs (modalities, environments, volumes, edge cases) that measurably improve model performance. Build detailed project plans, timelines, and operational workflows to ensure high‑quality, efficient data collection across real‑world, lab, and simulated environments. Stand up and refine pipeline infrastructure and processes with partner engineering teams so that data flows cleanly into annotation, training, and evaluation. Train, coach, and functionally lead distributed teams of operators, moderators, contributors, collectors and site staff executing collection campaigns. Build dashboards, analytics, and regular reports to guide data‑driven decisions on coverage, quality, throughput, and unit economics. Partner closely with Engineering, Product, Finance, and Go‑to‑Market to design and delivert solutions that drive both technical outcomes (better VLAs/VLMs, policies, world models) and business outcomes (revenue, margins, strategic wins). Provide clear, regular progress updates and risk/mitigation plans to leadership and other senior stakeholders. Contribute as a thought leader in Robotics & Physical AI by publishing blogs, talks, internal write‑ups, or open‑source artifacts that share learnings from our data, systems, and customer work.