Robotics Data Collection Manager

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of the complete delivery process for egocentric robotics data collection initiatives, from the initial kickoff to the final hour acceptance, ensuring that all client quality, diversity, and timeline objectives are achieved.

• Create and sustain a standardized collection playbook that can be tailored to meet varying client needs, such as camera geometry, naturalism blend, mount type, and geographic regions, rather than starting from scratch for each project.

• Develop reusable delivery materials, including SOPs, onboarding and training programs, scorecards, rubrics, and tracking systems to be shared across various client programs.

• Track daily project advancements against hourly targets and acceptance rates, proactively identifying and resolving bottlenecks to prevent delays in delivery.

• Respond to client QA feedback within 24 hours, providing actionable direction to contributors and driving measurable enhancements in quality, diversity, and adherence to tasks.

• Work closely with Robotics Solutions Engineers to ensure a seamless transition from pre-sales design to execution, aligning on scope, success metrics, and data collection strategies.

• Develop a practical understanding of client robotics architectures—including VLMs, VLAs, ACTs, world models, and manipulation policies—to convert model requirements into specific data collection guidelines.

• Convert client technical requirements (such as camera geometry, IMU specifications, naturalism targets, egocentric capture pipeline standards, and file format demands) into clear instructions for contributors and internal delivery standards.

• Collaborate with clients’ robotics and ML teams to grasp evolving data requirements and proactively modify collection programs to ensure the dataset's effectiveness for model training.

• Maintain expertise in egocentric capture best practices, sensor/rig setups, and common failure modes (like robotic movement issues, poor framing, and low task diversity) to improve quality from the outset.

• Manage a continuous recruitment process capable of sourcing and onboarding over 10,000 participants at scale across markets in the US, LatAm, and developed Asia.

• Partner with recruitment channels—including crowd work agencies, BPO and workplace partnerships, universities, gig platforms, and referral networks—to sustain a reliable and diverse sourcing pipeline.

• Design and implement participant onboarding and training programs that prioritize quality, addressing common failure issues before large-scale collection begins.

• Monitor contributor metrics such as acceptance rates, fraud rates, diversity scores, and hour contributions, taking corrective measures as necessary.

• Act as the primary operational liaison for robotics clients during active collection phases, fostering strong relationships and positioning Innodata for contract growth.

• Provide regular updates on project status to clients and internal leadership, including progress on hour delivery, acceptance rates, fraud rates, and outstanding issues.

• Bring structured, frontline feedback from clients into Innodata’s product and roadmap discussions, contributing to the development of a scalable Robotics & Physical AI data practice.

• Represent Innodata’s robotics data capabilities at significant industry events and contribute to thought leadership through presentations and published materials.

• Coordinate the procurement, configuration, shipping, and recovery of devices across collection regions, favoring company-owned, centrally managed iPhone fleets over participant-owned devices.

• Standardize on client-specified hardware rigs—such as head mounts and tilted-down geometry—while addressing known comfort issues through mount fitting, session length guidance, and participant training.

• Build and oversee a logistics function responsible for procuring, configuring, tracking, refurbishing, and redeploying devices across LatAm, Asia, and US markets.

• Implement fraud prevention protocols across the contributor base, ensuring that confirmed fraudulent sessions are flagged and not compensated, maintaining fraud rates below client thresholds.

• Foster a quality-first collection culture through training, real-time monitoring, and prompt feedback, treating QA as an upstream engineering challenge rather than a downstream fix.

• When clients provide backend QA access, integrate into the feedback loop to continuously refine training and delivery.

⛳️ Requirements

• A Bachelor's degree or higher in a relevant field.

• Over 5 years of experience in data collection, content operations, or program management, including at least 2 years of managing large-scale contributor or workforce programs.

• Practical experience with robotics or Physical AI systems—including perception/control stacks, egocentric data pipelines, teleoperation, or simulation—is strongly preferred.

• Familiarity with robotics model architectures (VLMs, VLAs, ACTs, world models) and the flow of training data requirements from model specifications.

• Experience in egocentric video data collection, computer vision datasets, or multimodal robotics training data.

• Strong operational and project management abilities, comfortable managing multiple concurrent workstreams across different regions with tight deadlines.

• Demonstrated capability to convert complex technical specifications into clear, actionable instructions for non-technical contributors.

• Experience working with clients in a B2B delivery context, possessing excellent communication skills for interactions with both senior executives and frontline engineers.

• Ability to work cross-functionally with Sales, Product, Engineering, and Operations in a fast-paced, ambiguous environment.

• Previous experience in data/AI/robotics delivery, solutions engineering, or technical program management is a significant advantage.

🏝️ Benefits

• Comprehensive health and wellness benefits.

• Opportunities for professional development and career advancement.

• Collaborative and innovative work environment.

• Flexible working hours and remote work options.