Machine Learning Engineer

Motional is a pioneering driverless technology company dedicated to making autonomous vehicles a safe, reliable, and accessible mode of transportation. As a joint venture between Hyundai Motor Group and Aptiv, Motional is at the forefront of innovation in the autonomous driving industry. Headquartered in Boston, with operations spanning the U.S. and Asia, the company has a proven track record of industry-leading achievements, including the first fully-autonomous cross-country drive in the United States, the launch of the world's first robotaxi pilot, and operating one of the longest-standing public robotaxi fleets globally. Motional's mission is to transform mobility by developing cutting-edge autonomous vehicle technology that enhances safety, creates equitable transportation options, and improves communities worldwide.

About the role

We are seeking a highly skilled Machine Learning Engineer to join our Data Mining team at Motional. In this role, you will be instrumental in developing the "brain" of our ML-powered multimodal data mining framework, Omnitag. Your primary focus will be on extracting valuable insights from vast amounts of multimodal sensor data, including vision and LiDAR, to identify critical edge cases, long-tail scenarios, and model errors that are vital for improving autonomous driving systems. You will work at the intersection of large-scale representation learning and data retrieval, building smarter data mining tools and efficient data pipelines. Your efforts will directly support model improvement cycles, post-training analysis, error diagnosis, and dataset curation. This role offers the opportunity to collaborate with cross-functional teams, implement scalable ML solutions, and contribute to the advancement of autonomous vehicle technology in a dynamic, innovative environment.

Responsibilities

• Develop, train, and fine-tune machine learning models for multimodal sensor data, emphasizing supervised and self-supervised learning techniques
• Implement scalable data preprocessing, augmentation pipelines, and optimize models for production environments using techniques such as batch inference and quantization
• Design and develop embedding-based search tools and active learning workflows to identify and analyze critical driving scenarios
• Create and maintain dashboards for monitoring model health, data drift, and system performance, and assist in operational support
• Adhere to best practices in software engineering, including version control, CI/CD, and comprehensive documentation
• Collaborate closely with senior engineers and ML teams to translate prototypes into scalable, maintainable solutions
• Participate in code reviews, contribute to technical documentation, and continuously improve development processes

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field
• Hands-on experience with PyTorch (preferred) or TensorFlow/JAX
• Proficiency in Python, with the ability to write clean, modular, and well-documented code
• Experience working with large datasets, including SQL, Pandas, and NumPy
• Knowledge of version control systems, unit testing, and software design patterns
• Understanding of the full ML lifecycle, from data cleaning and feature engineering to model validation and deployment
• Strong problem-solving skills and proactive learning attitude
• Excellent communication and collaboration skills

Benefits

• Competitive salary range of $144,000 to $192,000 USD
• Comprehensive health benefits including medical, dental, and vision insurance
• 401(k) plan with company matching contributions
• Health savings accounts (HSAs) and flexible spending accounts (FSAs)
• Life insurance and pet insurance options
• Paid time off and holidays
• Opportunities for professional development and career growth
• Hybrid work model with in-office collaboration at Boston, Pittsburgh, or Las Vegas locations, or fully remote options