Meta
Research Engineer, Robotics - Meta Superintelligence Labs
$122K–$181K
Menlo Park, CA · Full-time · Posted Aug 28, 2026
- Experience
- 1+ years in robotics or a related field, or an advanced degree with equivalent experience.
- Education
- Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience; also lists a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field. Degree must be completed prior to joining. PhD in computer science, robotics, AI, or related fields is listed.
About the job
Conduct fundamental and applied research to develop embodied AI and robotics capabilities, including algorithms, models, and systems for simulated agents and real robots.
What you'll do
- Research and develop AI algorithms and models for embodied intelligence.
- Create data-driven robotics methods using modalities such as images, video, text, audio, and tactile data.
- Build and benchmark capabilities for simulated agents and real robots, supporting long-term research goals.
What they ask for
- Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience; degree must be completed before joining.
- Experience in a listed research area, such as robotics, embodied AI, reinforcement learning, or vision-language models.
- Experience with machine learning models and frameworks such as PyTorch or TensorFlow.
- Proficiency in Python, C++, or similar; 1+ years of experience in robotics or a related field, or an advanced degree with equivalent experience.
Nice to have
- Experience with robotics frameworks such as ROS, robot simulations, and real-world hardware.
- Experience designing robotic systems or infrastructure and analyzing complex, large-scale data.
Pay
$121,992/year to $181,000/year (base salary)
Tools
PyTorch, TensorFlow, Python, C++, ROS
AI focus
Research and develop embodied AI, robotics, machine learning, and neural-network methods, including data-driven paradigms for simulated agents and real robots.
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