ML Engineer - Robotics

### 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. Originally posted on [Himalayas](https://himalayas.app)