Senior, Machine Learning Engineer

Responsibilities

• Design, develop, and deploy deep learning models for camera-based perception, including object detection, segmentation, depth estimation, and scene understanding.
• Own end-to-end model development from data curation and training through evaluation and deployment.
• Write production-quality machine learning code for scalable training, evaluation, and inference pipelines.
• Analyze model performance and failure modes across driving scenarios and improve robustness and generalization.
• Improve large-scale dataset preparation, distributed training, experiment tracking, tooling, workflows, and infrastructure.
• Partner with data teams on labeling strategies, dataset quality, and edge-case coverage.
• Collaborate with perception, simulation, and validation teams to evaluate and integrate models into the autonomy stack.
• Contribute to model architecture decisions and technical discussions.
• Mentor junior engineers on implementation, debugging, and best practices.

Requirements

• Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field plus 6+ years of industry experience; alternatively, a master’s degree plus 3+ years or a PhD plus 1+ years.
• Experience developing and deploying deep learning models for computer vision or perception systems.
• Strong programming skills in Python and PyTorch, including production-quality machine learning code.
• Experience training and evaluating models on large-scale datasets and distributed compute environments.
• Understanding of deep learning architectures used in perception, including CNNs, transformers, and multi-task models.
• Experience debugging model behavior, analyzing performance metrics, and improving model reliability.
• Ability to translate ambiguous problems into structured machine learning solutions and deliver independently.
• Experience collaborating cross-functionally to integrate machine learning models into autonomy or robotics systems.
• Preferred experience includes autonomous driving, robotics, simulation-based ML, multi-task learning, unified perception architectures, large-scale data pipelines, Ray, experiment-management frameworks, camera calibration, geometric reasoning, 3D perception, BEV, monocular depth, structure-from-motion, and production robotics deployments.

Benefits

• Hybrid work is available in the Ann Arbor, Michigan or Blacksburg, Virginia offices, or remotely within the United States.
• Competitive compensation includes a bonus component and stock options.
• Full-time employees receive 100% paid medical, dental, and vision premiums.
• 401(k) plan includes a 6% employer match.
• Flexible scheduling, generous paid vacation available immediately after start date, and company-wide holiday office closures.
• AD&D and life insurance are provided.