Staff ML Engineer - Robotics

What we’re doing isn’t easy but nothing worth doing ever is.

We envision a future powered by robots that work seamlessly with human teams. We build artificial intelligence that enables service robots to collaborate with people and adapt to dynamic human environments. Join our mission-driven venture-backed team as we build out current and future generations of humanoid robots.

As a Staff ML Engineer Perception / Robotics you will develop deploy and optimize machine learning models that enable robots to understand and navigate complex human environments. You will lead the design of ML systems from sensor fusion to real-time inference ensuring robustness in safety-critical real-world deployments.

Responsibilities

• Develop and deploy ML models for perception/navigation tasks such as object detection semantic segmentation tracking scene understanding localization and path prediction.

• Design and implement sensor fusion and mapping pipelines combining vision depth LIDAR IMU and other signals for robust perception and navigation in dynamic spaces.

• Build real-time ML inference pipelines optimized for robotic hardware and embedded compute.

• Setup data collection labeling strategies dataset curation and synthetic data augmentation for training and evaluation.

• Establish metrics benchmarks and test frameworks to validate ML models in both simulation and real-world environments.

• Collaborate with robotics software engineers to integrate perception and navigation intelligence into autonomy stacks.

• Work with operations to analyze field data diagnose performance gaps and iterate on model improvements.

• Contribute to long-term ML and perception and navigation architecture decisions influencing the roadmap for future robots.

• Mentor junior ML engineers and contribute to building strong applied ML best practices within the team.

Skills and Experience

• Master’s or PhD in Computer Science Robotics Machine Learning or related field.

• 8+ years of experience in applied machine learning computer vision or robotics perception.

• Strong background in deep learning frameworks (PyTorch TensorFlow JAX).

• Hands-on experience with real-time perception/navigation tasks (detection tracking segmentationpath planning).

• Expertise in one or more sensor modalities: RGB/depth cameras LIDAR radar or multimodal fusion.

• Experience deploying ML models on edge/embedded hardware (e.g. Jetson TPU ARM-based platforms).

• Familiarity with SLAM mapping and navigation pipelines.

• Solid software engineering skills in Python and C++ for ML system integration.

• Proven ability to take ML models from research prototype to production deployment.

• Strong debugging skills for diagnosing ML performance gaps in fielded systems.