Senior Machine Learning Engineer (Data Mining) - Hybrid

About the Role

Motional is building the next generation of autonomous driving intelligence by uncovering rare edge cases and long-tail scenarios hidden in massive multimodal sensor data. As a Senior Machine Learning Engineer on our Data Mining team, you’ll help develop the “brain” behind Omnitag—an ML-powered multimodal data mining framework.

You will design large-scale multimodal Teacher models that learn rich representations of the world, then distill them into highly efficient Student models capable of scanning vast datasets in near real time.

Responsibilities

• Design and train multimodal Teacher models for representation learning and world understanding
• Develop distillation and optimization approaches to create hyper-efficient Student models
• Work on retrieval optimization and reasoning systems to improve discovery of high-value scenarios
• Build and iterate on large-scale pipelines for multimodal training, evaluation, and data mining
• Collaborate with cross-functional teams to translate model performance into practical intelligence for autonomous systems

Requirements

• Strong experience in machine learning with a focus on large-scale representation learning
• Proficiency in retrieval optimization, ranking/search, or related information retrieval techniques
• Experience with model distillation and/or efficiency-focused model training (e.g., compression, acceleration)
• Hands-on background building and deploying ML systems at scale
• Strong coding skills and familiarity with modern ML frameworks and tooling

Benefits

• Opportunity to work on mission-critical autonomous driving intelligence and high-impact ML research
• Collaborate with a team focused on scalable multimodal learning and real-world performance
• Competitive compensation and comprehensive benefits package (details to be shared during the process)