Machine Learning Engineer, Data Mining

Mission Summary

At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.

As a Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine. You will work with state-of-the-art foundation models to extract insights from driving data, operating at the intersection of large-scale representation learning and data retrieval. By building smarter mining tools and efficient data pipelines, you will accelerate the model improvement lifecycle for post-training analysis, error diagnosis, and dataset curation.

What You'll Do

• Build and Train ML Pipelines: Develop, train, and fine-tune models for multimodal sensor data (e.g., vision, LiDAR) using supervised and self-supervised learning.
• Support Model Deployment: Implement scalable preprocessing and augmentation pipelines and apply optimization techniques such as batch inference and quantization.
• Data Mining & Analysis: Develop embedding-based search tools and active learning workflows to identify critical driving scenarios.
• Monitor Production Performance: Build dashboards to monitor model health, data drift, and system performance; identify regressions and support operations.
• Engineering Best Practices: Follow standards including version control, CI/CD, and unit testing; participate in code reviews and documentation.
• Collaboration: Translate ML prototypes into scalable, maintainable engineering solutions with cross-functional teams.

What We're Looking For (Must-Haves)

• BS or MS in Computer Science, Machine Learning, or related field
• Hands-on experience with PyTorch, TensorFlow, or JAX
• Strong proficiency in Python
• Experience with large datasets, including SQL, Pandas, and NumPy
• Knowledge of version control, unit testing, and software design patterns
• Understanding of the full ML lifecycle from data preparation to deployment
• Proactive mindset and ability to thrive on feedback

Bonus Points

• MS/PhD in Computer Science, Machine Learning, or related field
• Experience with agentic systems, LLM-based planning, or autonomous reasoning
• Background in autonomous driving, robotics, or real-time systems
• Familiarity with multimodal learning, sensor fusion, or embodied AI
• Experience with active learning and ML-based data mining
• Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms
• Publications in ICCV, CVPR, ECCV, or similar conferences

Salary Range

$144,000—$192,000 USD

Benefits

• Medical, dental, and vision insurance
• 401k with company match
• Health saving accounts
• Life insurance
• Pet insurance
• Additional employee benefits