About the Role

We are a Series A AI/ML data and services company building highly accurate AI through high-quality training data, robust reinforcement learning environments, and intelligent agents for frontier labs and enterprises. Our work spans the full AI lifecycle — from data labeling and post-training to evaluation and deployment — with a strong focus on physical intelligence and embodied AI.

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 will build perception, planning, and decision-making pipelines that make machines truly adaptive, collaborating with world-class AI teams to solve hard, interdisciplinary problems that combine data-driven learning with real-world 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.

• Collaborate with robotics and hardware engineers to deploy models in live environments.

• Continuously evaluate model performance and robustness across diverse real-world scenarios.

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 (Gazebo, Isaac Sim, CARLA, MuJoCo, 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 deployments.

Nice to Have:

• Familiarity with localization, SLAM, or adaptive control techniques.

• Experience with imitation learning or model-based reinforcement learning.

• Background deploying ML models in real-time or embedded environments.

Eligibility: Candidates must be eligible to work in the United States without company visa sponsorship. No visa sponsorship is available for this role.

Compensation & Benefits

• Salary range: $220,000 – $300,000 USD annually, depending on experience.

Location

This is a fully on-site role based in Mountain View, CA. Local candidates or those willing to relocate are preferred; remote work arrangements are not available for this position.