ML Engineer

Project Description

This team is working with an AI chip company that develops specialized software-centric Machine Learning Systems-on-Chip (MLSoC) to enable high-performance, power-efficient "Physical AI" at the edge. Their technology is designed for robotics, autonomous vehicles, and smart cameras, allowing them to process complex computer vision and multimodal AI tasks locally with very low power consumption.

Job Description
The ideal candidate is an ML engineer with a strong background in autonomous systems and mobile robotics. The role requires someone who has spent meaningful time training ML models for complex autonomous platforms—focusing on perception, navigation, and control in GPS-denied, high-speed, and visually complex environments.

The candidate must have hands-on production experience with NVIDIA Isaac Sim and the Omniverse ecosystem, including building photorealistic simulation environments, running Omniverse Replicator synthetic data pipelines for perception, and closing the sim-to-real gap on real robotic hardware. Experience with reinforcement learning or imitation learning for navigation policies is required—specifically training agile navigation policies in simulation and validating them on hardware. A background from an autonomous robotics company, a research group, or an embodied AI team is a must.

On the ML side, the candidate will own the full perception model pipeline: training and fine-tuning visual-inertial odometry components, stereo depth estimation, and defect detection models on synthetic sensor data generated in Isaac Sim; quantizing those models to INT8/BF16 for deployment on the customer MLA; and profiling MLA utilization across navigation, inspection, and complex tracking use cases. The candidate will be the first to apply the custom Palette toolchain to a robotics AI stack—a genuinely novel workload requiring comfort navigating a custom MLA compiler with limited prior art. Strong PyTorch proficiency, familiarity with autonomous control stack integration, and a demonstrated track record of deploying perception models on real-world hardware are essential.

Job Responsibilities

We are seeking an exceptional Senior/Principal Engineer, Robotics Software to join our cutting-edge Robotics and AI software team. The ideal candidate brings deep, hands-on experience in autonomous mobile robots (AMRs), aerial robots. 

• Drive technical discussions relating to architecture, design, and development of software and hardware systems for AMRs, and/or humanoid robots.
• Build and deploy perception, localization, and navigation systems using Lidar-based and Visual SLAM techniques.
• Integrate deep learning models for object detection, motion planning, behavior prediction, and scene understanding.
• Contribute to or lead R&D efforts related to Generative AI and its applications in robotics.
• Collaborate with cross-functional teams including electrical engineers and AI scientists to deliver complete solutions.
• Mentor junior engineers and provide strategic input into long-term robotics and AI vision.