Robotics Research Engineer

Role Overview

This remote role is centered on improving how embodied robotics data is captured, organized, and applied to strengthen AI training and perception systems. You will work with research-focused teams to shape data structures, collection approaches, and evaluation methods that support the next wave of robotic learning. The work contributes to how AI models are trained and used in real-world settings across fields such as healthcare and engineering by enabling datasets that are scalable, varied, and high quality.

Key Responsibilities

• Create and maintain consistent robotics data formats, schemas, and benchmarks so information is represented in a reliable and standard way.
• Develop and test modern data collection approaches such as human demonstrations, teleoperation, and multi-sensor setups.
• Work closely with teams across engineering, AI research, and data science to ensure robotics data pipelines match model-training needs.
• Assess datasets for breadth, scale, and usefulness to make sure they meaningfully improve AI systems.
• Build prototypes, experiments, and internal tools that make data gathering more efficient, drawing on proven practices from leading robotics research environments.

Required Background

• At least 2–5+ years of experience in robotics R&D, data engineering, or applied research with exposure to data pipelines and multimodal schemas.
• Solid understanding of robotics data types such as RGB-D, IMU, pose, and language, and how they support perception and control.
• Practical experience with robot perception, control methods, or data-driven learning in either a research or industry environment.
• Strong collaboration and communication abilities, especially when working across technical disciplines.
• Degree in robotics, computer science, electrical engineering, or a closely related technical discipline.

Additional Information

This opportunity gives you the chance to help build a scalable platform used for AI training by leading labs and enterprises. The role also involves exposure to advanced robotics datasets, reinforcement learning environments, and evaluation methods designed to improve model performance across different use cases.

Equal Opportunity

Hiring is based on demonstrated skill and expertise. Candidates from all backgrounds are encouraged to apply, and decisions are made without regard to prior work history or personal background.