Machine Learning Engineer

Role Overview

Machine Learning Engineer to join Motional’s Data Mining team. Build the “brain” of Omnitag, an ML-powered multimodal data mining framework that extracts insights from large-scale vision and LiDAR sensor data to improve autonomous driving systems.

Responsibilities

• Develop, train, and fine-tune ML models for multimodal sensor data, emphasizing supervised and self-supervised learning
• Build scalable data preprocessing and augmentation pipelines; optimize for production using batch inference and quantization
• Design embedding-based search tools and active learning workflows to find and analyze critical edge cases, long-tail scenarios, and model errors
• Create and maintain dashboards to monitor model health, data drift, and system performance; support operational needs
• Apply software engineering best practices: version control, CI/CD, and strong documentation
• Collaborate with senior engineers and ML teams to scale prototypes into maintainable solutions; participate in code reviews and technical documentation

Requirements

• BS or MS in Computer Science, Machine Learning, or related field
• Hands-on experience with PyTorch (preferred) or TensorFlow/JAX
• Proficiency in Python with clean, modular, well-documented code
• Experience with large datasets using SQL, Pandas, and NumPy
• Knowledge of version control, unit testing, and software design patterns
• Understanding of the full ML lifecycle: data cleaning, feature engineering, model validation, and deployment
• Strong problem-solving skills and proactive learning mindset
• Good communication and collaboration skills

Nice-to-Haves / Implied Skills

• Experience building embedding-based retrieval/search systems
• Familiarity with ML monitoring practices (e.g., model health and data drift)

Benefits (as stated)

• Competitive salary: $144,000–$192,000 USD
• Medical, dental, vision insurance
• 401(k) with company matching
• Health savings accounts (HSAs) and flexible spending accounts (FSAs)