Machine Learning Engineer - Remote

Role Overview

Join Motional’s Data Mining team as a Machine Learning Engineer. You’ll help develop the Omnitag framework—an ML-powered multimodal data mining system—and build models that extract insights from large-scale sensor data (notably vision and LiDAR) to improve autonomous driving safety and reliability.

Responsibilities

• Develop, train, and fine-tune machine learning models for multimodal sensor data (vision, LiDAR)
• Build scalable preprocessing and augmentation pipelines to support deployment
• Apply optimization techniques such as batch inference and quantization for production efficiency
• Design embedding-based search tools and active learning workflows to find critical driving scenarios
• Monitor model performance in production, including data drift and system health metrics
• Build dashboards/tools for operational support and performance tracking
• Follow software engineering best practices: version control, CI/CD, documentation, unit testing
• Collaborate with senior engineers and cross-functional teams to scale prototypes

Requirements

• BS or MS in Computer Science, Machine Learning, or related field
• Hands-on experience with PyTorch (preferred) or TensorFlow/JAX
• Strong Python skills for clean, modular, well-documented code
• Experience with version control, unit testing, and software design patterns
• Experience with large datasets, including SQL, Pandas, and NumPy
• Understanding of the full ML lifecycle (data cleaning → feature engineering → deployment)
• Strong analytical skills and a proactive learning mindset

Nice-to-haves / Focus Areas

• Large-scale representation learning and data retrieval for multimodal mining
• Building systems that identify edge cases, long-tail scenarios, and model errors