Robotics AI Research Engineer

About the Role

We are seeking exceptional AI researchers and engineers to architect the neural backbone of our general-purpose robots. You will design the Vision-Language-Action (VLA) frameworks or Action World Models that allow our robots to reason, adapt, and succeed where traditional automation fails.

We are hiring across all levels (from early-career to staff/principal). You are not expected to be a master of every domain listed below; however, you must be able to justify world-class excellence in at least one core factor (e.g., model architecture, RL formulations, or high-scale data systems).

What You’ll Do

• Architect Embodied Foundations: Design model architectures (VLA, World Models, etc.) that achieve ultra-high task success rates with minimal human demonstrations
• Master Data Efficiency: Develop novel co-training strategies and efficient learning algorithms that leverage diverse data sources—from Internet-scale video to sparse, high-fidelity human interventions
• Generalize Cross Embodiments: Build models capable of zero-shot or few-shot adaptation to new robot configurations, maintaining a high success rate even when proprietary hardware and actuation systems evolve
• Innovate Real-World RL: Formulate and deploy novel Reinforcement Learning and policy extraction methods specifically designed for physical, real-world manipulation
• Design the Data Loop: Collaborate on advanced data collection systems to capture critical human intervention data for model bootstrapping

What We’re Looking For

• MS or PhD in CS, Robotics, Machine Learning, or a related field (or equivalent industry experience)
• Deep Technical Mastery: Advanced understanding of transformers, multi-modal alignment, and mapping perception to high-frequency motor control
• Specialized Excellence: Proven ability to innovate—not just implement—within one or more areas: VLA models, Real-world RL, or large-scale Data Infrastructure
• Software Excellence: Expert-level Python and deep familiarity with PyTorch or JAX

Nice to Have

• A track record of high-impact publications (NeurIPS, ICRA, RSS, CVPR) or significant open-source contributions
• Experience with large-scale distributed training and model compression
• Experience with deployment of models to edge devices (NVIDIA Jetson/Orin) for real-time inference
• General knowledge of robotics principles (kinematics, dynamics)