Data Quality Assurance Specialist

Who We Are

We are a rapidly growing embodied AI company revolutionizing human labor. Leveraging cutting‑edge robotics and advanced artificial intelligence, we develop transformative technologies that redefine how work is done across multiple industries—empowering businesses to streamline operations, boost productivity, and unlock new possibilities.

Overview

As a Quality Assurance Specialist in our Data Generation team within R&D, you will play a central role in ensuring the reliability and accuracy of the datasets used to train our next‑generation embodied AI models. You will own the quality layer across teleoperation data, labeled datasets, and custom data‑collection pipelines produced by our Teleoperations & Data Labelling. Your work directly influences model performance, robustness, and generalization in real‑world environments. This is a high‑impact role at the intersection of data operations, robotics R&D, and product quality.

Your Responsibilities

Data Quality Assurance (Primary Focus)

• Review, validate, and approve data batches from teleoperation and labeling teams.
• Ensure accuracy, completeness, consistency, and correct formatting across all data types.
• Identify quality issues early and maintain clear rejection/acceptance criteria.
• Analyze recurring error patterns and enforce corrective measures.
• Conduct systematic audits of annotations, teleop sequences, metadata, and structured datasets.
• Track quality metrics and maintain reports on performance trends across contributors.
• Safeguard the reliability of all datasets entering R&D and model training pipelines.

Process, Enablement & Collaboration

• Develop and refine QA workflows, checklists, and annotation guidelines.
• Train teleoperators and labelers on quality standards, edge cases, and best practices.
• Provide structured feedback and contribute to onboarding new team members.
• Work closely with ML and Robotics teams to understand data requirements and evolving quality thresholds.
• Support improvements to annotation tooling and teleoperation UX based on QA findings.
• Ensure smooth communication between Data Generation, Teleoperations, and R&D.

Qualifications

Education And Experience

• Bachelor’s degree in a relevant field (Computer Science, Cognitive Science, Data Science, Robotics, or similar).
• Experience in data annotation, teleoperations environments, ML datasets, or related QA/operations roles is a strong plus.
• Experience with structured QA processes or quality control frameworks is beneficial.

Skills

• Strong attention to detail and an ability to spot inconsistencies in complex datasets.
• Familiarity with data annotation tools, teleoperation interfaces, or dataset management workflows.
• Understanding of basic ML concepts and why data quality matters for model performance.
• Ability to design and enforce clear QA guidelines and processes.
• Proactive communicator with the ability to teach, coach, and align multiple stakeholders.
• Comfortable working in fast‑moving environments with evolving requirements.

Our interview plan

• Application
• Take‑home assignment: You’ll work on a short, role‑relevant task with clear instructions and a deadline.
• Cultural fit interview (40 min): A conversation about how you work, what motivates you, and what you’re looking for. Expect CV highlights, your “why,” and time for your questions.
• Technical fit interview (45 min): A deeper dive into your skills and problem‑solving approach for this role.
• Onsite Visit & Founder interview (30 min): A discussion on vision, impact, and how the role connects to company priorities.

What we offer

• Wellpass (gym membership)
• Free meals at the workplace
• Flexible working hours
• Option to work from home when needed
• A motivated team and an open corporate culture
• Competitive compensation and excellent career development opportunities

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