Innodata Inc.
Robotics Solutions Engineer – Robotics Data Collection & Physical AI
Remote - United States · Senior
Sponsorship not specified$150k-$230kDetected 23 days ago
PythonJavaC++LinuxMachine LearningData EngineeringLLMsRoboticsResearchCommunication
About the role
- This is a high‑visibility role that directly influences strategic deals and long‑term partnerships.
Responsibilities
- Proven ability to manage complex technical projects, juggle multiple customer engagements, and operate with a strong sense of ownership and attention to detail.
- Familiarity with large‑scale dataset design, evaluation frameworks, or robotics data marketplaces.
- Work closely with Engineering and Product to design and implement robotics data capture solutions (real‑world, lab, and simulation), including sensors/rigs, teleop/UMI flows, and egocentric capture pipelines.
- Design and run customized demos, playbooks, and experimental workflows that showcase robotics data capabilities and shorten the time from idea to production pilot.
- Collaborate closely with Robotics Project Leads to ensure clean handoff from pre‑sales design to delivery, align on scope and success metrics, and support smooth execution of data collection programs.
Requirements
- Hands‑on experience with robotics or Physical AI systems (e.g., perception/control stacks, teleoperation, simulation, or robotics data pipelines).
Nice to have
- 3+ years of experience developing with Python and one or more additional languages commonly used in robotics/ML (e.g., C++, Java), plus comfort working in Linux‑based environments.
Compensation
- The expected salary range for this position is $150,000 – $230,000 USD per year, based on experience, skills, and qualifications.
Company info
- Experience selling or supporting complex technical solutions with enterprise customers.
- Collaborate with Innodata Client Partners to scope and deliver technical pilots and POCs, earning the "technical win" with new and existing robotics customers.
- Collaborate directly with customers' robotics and ML teams to understand their architectures (VLMs, VLAs, ACTs, world models, policies), define data and evaluation requirements, design execution plans, and translate them into actionable Statements of Work.
- Bring structured, frontline feedback from customers back into Innodata's product and roadmap discussions, helping shape a scalable Robotics & Physical AI data practice and platform.
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