Job Description
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
