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- Expérience
- 2 ans et plus
- Salaire
- USD 400,000 – USD 1,500,000 / year
- Ouvertures
- 1
- Publié
- il y a 1 mois
- Mode de travail
- Travaillez à domicile
- Éducation
- Robotics, Computer Science, Electrical Engineering, or a related field
- Admissibilité
- Candidates with a background in Robotics, Computer Science, Electrical Engineering, or a related field, and at least 2 years of relevant experience in robotics R&D, data engineering, or applied research can apply.
- CV
- Candidature requise
Description de l'emploi
Role Overview
This is a full-time remote position for a Robotics Lab Member of Technical Staff focused on improving how robotics data is defined, collected, and used for training. The role centers on creating stronger data foundations for robot learning and experimentation.
Compensation
The annual pay range for this position is $400K to $1.5M.
Key Responsibilities
- Create and maintain clear robotics data structures, schemas, and benchmarks so information is easier to use and compare.
- Develop new approaches for gathering data, including human demonstrations, teleoperation, and sensor-based input.
- Work closely with teams across functions to make sure training data needs are properly aligned.
- Review datasets for variety, ability to scale, and overall usefulness in improving robot learning.
- Build prototypes, experiments, and internal tools that make data collection faster and more efficient.
- Keep track of progress in leading robotics research groups and bring useful practices into the workflow.
Requirements
- At least 2 years of experience in robotics R&D, data engineering, or applied research.
- Strong understanding of robotics data pipelines and multimodal formats such as RGB-D, IMU, pose, and language.
- Hands-on exposure to robot perception, control, or data-driven learning methods.
- A degree in Robotics, Computer Science, Electrical Engineering, or a similar discipline.
- Prior experience with top robotics or AI organizations is an advantage, as is familiarity with embodied AI datasets or imitation learning workflows.
Application Process
- Submit an application through the available application channel.
- Monitor email for follow-up instructions.
- Complete resume screening and participate in the interview process.