About the Role

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.

What You'll Do

• 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.

What We're Looking For

Required

• 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.

Compensation & Benefits

• Salary: $220,000 – $300,000 USD annually, commensurate with experience.

Location

• On-site in Mountain View, CA. Local candidates or candidates willing to relocate are required. Remote work is not available for this position.

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