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, labelled 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