Logo for 24-MAG

Remote | Member of Technical Staff, Robotics Research — $500,000–$1,500,000/year

Role overview

Qualifications

  • 2–5+ years of experience in robotics, computer vision, multimodal learning, or closely related field
  • Strong understanding of robotics, physical AI, and multimodal data
  • Degree in Robotics, Computer Science, Electrical Engineering, Machine Learning, or equivalent practical experience

Responsibilities

  • Research the data requirements of frontier robotics and embodied AI systems
  • Design datasets and collection methodologies for advanced robotics applications
  • Define data schemas, annotation structures, and ground-truth standards
  • Collaborate across research, engineering, operations, and data functions

Key facts

Hard skills

Other skills

  • Collaboration
  • Research
  • Communication

About the company

24-MAG logo

24-MAG

Business Consulting & Services

Company details

IndustryBusiness Consulting & Services
Company size2 - 10

Your match analysis

See how your profile stacks up against this role.

We compared the job requirements to your profile to show where you're strong and where you fall short.

Job 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

Ideal Profile

  • 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

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy

Apply once. Then go straight to the hiring manager.

After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.

MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
Unlocked after you apply
·

Related jobs

Other jobs at 24-MAG

Premium

Reach out to the hiring manager directly.

Gain access to the contact details of the hiring managers who actually decide, and reach out to network with them directly. That, plus more when you upgrade:

  • Full match report with fit score and gaps
  • Career diagnostics on how recruiters read you
  • Curated company matches and warm intros
  • 48h early access to new roles

Cancel anytime.