[Hiring] Member of Technical Staff, Robotics Research @24-MAG

Role Description

We are sharing a full-time opportunity for an experienced robotics researcher with strong expertise in robotics data, robot perception, multimodal learning, embodied AI, schema design, and robotics R&D to help design the datasets, collection methods, and evaluation frameworks that support next-generation robot learning and physical AI systems.

The role sits at the intersection of robotics, embodied AI, and data. The successful candidate will translate frontier research questions into scalable data strategies, experimental frameworks, and structured datasets spanning video, sensors, trajectories, teleoperation, simulation, and other modalities used in modern robotics research.

Key Responsibilities

• Robotics Data Research
  • Research the data requirements of frontier robotics, embodied AI, world models, and physical AI systems
  • Identify which forms of data are most useful for improving robot learning and perception
  • Analyse how dataset composition, structure, and diversity affect model performance
  • Translate emerging research needs into concrete data strategies
  • Help define scalable approaches to robotics data acquisition and evaluation
• Dataset & Collection Method Design
  • Design datasets and collection methodologies for advanced robotics applications
  • Work across egocentric video, teleoperation, UMI, robot trajectories, sensor data, and simulation
  • Define collection protocols that support repeatability, scalability, and research quality
  • Develop specifications for diverse physical and simulated environments
  • Evaluate trade-offs across different data-collection approaches
• Schema, Annotation & Evaluation Design
  • Define data schemas, annotation structures, and ground-truth standards
  • Create evaluation frameworks for manipulation, navigation, spatial reasoning, and physical understanding
  • Specify metadata and labels needed for multimodal robotics datasets
  • Design consistent structures across video, sensor, trajectory, and simulation data
  • Ensure datasets are suitable for model training, benchmarking, and research experimentation
• Experimentation & Model Performance Analysis
  • Run experiments to determine which data structures and collection approaches improve model performance
  • Evaluate the impact of different modalities, annotations, and dataset compositions
  • Develop hypotheses around robot-learning and perception performance
  • Interpret experimental results and recommend changes to data strategy
  • Support iterative improvement of data pipelines and research methodology
• Robotics R&D Collaboration
  • Work with advanced AI and robotics teams to translate research problems into data products
  • Collaborate across research, engineering, operations, and data functions
  • Communicate experimental findings and technical trade-offs clearly
  • Help convert frontier robotics research into scalable operational workflows
  • Stay current with developments in robotics, embodied AI, world models, and physical AI

Qualifications

• 2–5+ years of experience in robotics, computer vision, multimodal learning, embodied AI, applied ML research, or a closely related field
• Strong understanding of robotics, physical AI, and multimodal data
• Ability to translate research questions into datasets, experiments, schemas, and technical specifications
• Strong technical communication and cross-functional collaboration skills
• Degree in Robotics, Computer Science, Electrical Engineering, Machine Learning, or a related field, or equivalent practical experience
• Experience at a leading robotics, AI, autonomous-systems company, or research lab is highly valuable
• Hands-on experience with embodied AI datasets, imitation learning, teleoperation, or robot-learning pipelines is advantageous
• Experience designing or working with multimodal robotics datasets involving video, sensors, trajectories, or simulation is highly relevant
• Familiarity with robotics hardware, sensor integration, or rapid prototyping is beneficial
• Experience with data collection or evaluation for manipulation, navigation, spatial reasoning, or world models is a strong plus

Engagement Details

• Full-time engagement
• Fully remote
• Base compensation: $500,000–$1,500,000/year
• Work will involve robotics data research, dataset design, schema development, multimodal evaluation, experimentation, and collaboration with advanced robotics and AI teams
• Strong expertise in embodied AI, perception, robot learning, or robotics data is central to this role
• Assignments may involve egocentric video, teleoperation, robot trajectories, sensor data, simulation, manipulation, navigation, and world-model research
• Technical priorities and research scope may evolve as robotics and physical-AI initiatives develop