Data Operations Associate

Ultra • Brooklyn, OH

9d • Remote

About The Position

High-quality data is foundational to how we improve our robots. Every day, our systems perform a wide range of industrial tasks, generating large volumes of teleoperation, annotation, and performance data. We are looking for a Data Operations Associate to help ensure that this data is accurate, consistent, and useful for training better robot policies.
This role is split between data quality assurance and pilot operations. Roughly half of your time will be spent reviewing robot task data and annotations, identifying quality issues, providing clear feedback to annotators, and helping improve the guidelines and processes used to produce high-quality datasets. The other half will focus on teleoperation operations: observing pilots as they learn new tasks, evaluating their performance, and providing coaching and feedback that helps them operate robots more safely, consistently, and effectively.
This is a hands-on role for someone who is highly attentive, operationally rigorous, and excited to develop a deep understanding of how robot behavior, human performance, and data quality fit together. You will work closely with our Autonomy and Operations teams, and your work will directly affect the quality of the data used to train and evaluate our models.

Requirements

• Exceptional attention to detail and the ability to maintain consistent judgment while reviewing large volumes of complex information.
• Strong written and verbal communication skills, especially the ability to explain errors clearly and provide direct, constructive feedback.
• Comfort reviewing repetitive work without losing focus, while still recognizing unusual edge cases and broader patterns.
• A systems-oriented mindset: you look beyond individual mistakes to identify why they are happening and how the process can be improved.
• Comfort working with technical tools, structured data, spreadsheets, dashboards, and unfamiliar software systems.
• Good judgment and a willingness to make decisions when guidelines do not perfectly cover the situation.
• An interest in robotics, artificial intelligence, industrial operations, or the role high-quality data plays in improving machine-learning systems.
• A hands-on attitude. You are willing to perform a process yourself, understand it deeply, and help improve it before attempting to automate or delegate it.
• Comfort traveling to Mexico on a semi-regular basis, typically once a month or every other month, to work directly with pilot and data-operations teams.

Nice To Haves

• Experience in data operations, quality assurance, data annotation, technical operations, robotics operations, manufacturing, logistics, or another detail-oriented operational environment.
• Experience reviewing or producing labeled datasets for machine learning.
• Experience in robotics, teleoperation, manufacturing, warehouse operations, or industrial environments.
• Experience training, coaching, or evaluating operators.
• Experience working with external annotation or operations vendors.
• Familiarity with data-quality metrics, sampling methods, inter-annotator agreement, or quality-control workflows.
• Spanish-language proficiency.

Responsibilities

• Robot data quality assurance. Review videos and associated annotations from a high mix of industrial robot tasks. Identify missing, inaccurate, or inconsistent annotations and determine whether collected data meets established quality standards.
• Annotation feedback and improvement. Provide clear, structured feedback to internal and external annotation teams. Track recurring sources of error and help ensure that feedback leads to measurable improvements in annotation quality.
• Annotation guidelines. Help design, test, and refine annotation instructions, examples, rubrics, and edge-case guidance so that annotators can make consistent decisions at scale.
• Pilot observation and coaching. Observe teleoperation pilots as they train on new tasks, identify performance gaps, and provide timely, actionable coaching.
• Pilot readiness and evaluation. Help evaluate whether pilots are ready to perform tasks independently. Support the development of task-specific training materials, grading criteria, and certification processes.
• Quality monitoring and reporting. Track data-quality and pilot-performance metrics, investigate unexpected changes, and communicate findings to operations and technical stakeholders.
• Process improvement. Identify inefficient or unreliable parts of the data collection and review process, propose improvements, and help implement systems that maintain quality as operations scale.
• Cross-functional collaboration. Partner with the Autonomy team to understand which mistakes matter most for model training and evaluation, then translate those needs into practical guidance for pilots and annotators.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed