Member of Technical Staff (Robotics Lab) | $20-$50/hr Remote
Overview
This role focuses on defining the future of robotics data as a Robotics Researcher. You will work at the forefront of R&D, shaping how embodied data is collected, structured, and used for robot learning and perception. The position involves standardizing data formats, designing innovative collection methods, and collaborating with cross-functional teams to drive breakthroughs in AI training.
What You'll Do6
- 1Define and standardize robotics data formats, schemas, and benchmarks
- 2Design innovative data collection methods (human demos, teleop, sensors)
- 3Collaborate with cross-functional teams to align on model training data
- 4Evaluate datasets for diversity, scalability, and impact
- 5Prototype experiments and tools for efficient data gathering
- 6Stay updated on leading labs (Tesla, Figure, 1X) and integrate best practices
Requirements5
- 12–5+ years in robotics R&D, data engineering, or applied research
- 2Strong grasp of robotics data pipelines and multimodal schemas (RGB-D, IMU, pose, language)
- 3Experience in robot perception, control, or data-driven learning
- 4Excellent communication and cross-disciplinary collaboration skills
- 5Degree in Robotics, Computer Science, Electrical Engineering, or related field
Who Should Apply
The ideal candidate has a strong background in robotics R&D and data engineering, with deep experience in multimodal data pipelines and robot perception. You should be passionate about advancing robot learning and be comfortable prototyping data collection tools. Familiarity with embodied AI datasets or experience at top robotics companies is a plus.
Salary Insight
Base salary range $240,000 – $320,000 USD, plus equity compensation and performance-based bonuses. Comprehensive benefits include up to 100% reimbursement for health-insurance premiums, paid time off, 401(K) plan with company match.
Required Skills
Application Tip
Highlight your hands-on experience with robotics data pipelines and multimodal sensor schemas (e.g., RGB-D, IMU). Mention any work with imitation learning or embodied AI datasets to demonstrate alignment with the role's focus on data-driven robot learning.