ML Engineer - Robotics

Role Summary

We are a Series A AI company based in Mountain View, CA, building high-quality training and post-training data, robust reinforcement learning environments, and intelligent agents that bridge the gap between AI research and real-world execution. Our work spans multimodal data, agentic systems, and physical intelligence — and we collaborate closely with frontier AI labs and enterprises.

As an ML Engineer – Robotics , you will design, train, and deploy intelligent models that power autonomous systems at the intersection of machine learning, control systems, and real-world robotics. You'll build perception, planning, and decision-making pipelines that make machines truly adaptive, solving hard, interdisciplinary problems that combine data-driven learning with real-world physical constraints.

Responsibilities

• Develop and optimize ML models for perception, motion planning, and control.
• Build computer vision and sensor fusion systems using camera, LiDAR, and IMU data.
• Integrate learning-based models with robotics software stacks (ROS/ROS2).
• Design pipelines for data collection, simulation, and reinforcement learning workflows.
• Collaborate with robotics and hardware engineers to deploy models in live, real-world environments.
• Continuously evaluate model performance and robustness across diverse scenarios and deployments.

Requirements

• 3–8 years of professional experience in Machine Learning, Robotics, or Computer Vision.
• Proficiency in Python and C++ for robotics and ML development.
• Hands-on experience with PyTorch and/or TensorFlow for model development.
• Proficiency with ROS or ROS2 and integrating ML models into robotics software stacks.
• Experience with robotics simulation and benchmarking tools such as Gazebo, Isaac Sim, CARLA, MuJoCo, or PyBullet .
• Experience designing and deploying perception, motion planning, and control pipelines for autonomous systems.
• Experience with sensor fusion using camera, LiDAR, and IMU data.
• Experience with data collection pipelines, simulation environments, and reinforcement learning workflows.
• Strong ability to evaluate model performance and robustness across diverse real-world scenarios.

Nice to Have

• Familiarity with reinforcement learning, imitation learning, or adaptive control techniques.
• Background in localization, SLAM, or advanced control systems.
• Passion for embodied intelligence and pushing the boundaries of autonomous systems.

Eligibility

• Must be eligible to work in the United States without company visa sponsorship. Visa sponsorship is not available for this role.
• Salary: $220,000 – $300,000 USD annually, commensurate with experience.
• On-site in Mountain View, CA. Local candidates or candidates willing to relocate are required. Remote work is not available for this position.