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. As a Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine.

• Build and Train ML Pipelines: Develop, train, and fine‑tune models for multimodal sensor data (vision, LiDAR). Implement supervised and self‑supervised learning.
• Support Model Deployment: Create scalable data preprocessing, augmentation pipelines; apply optimization techniques (batch inference, quantization).
• Data Mining & Analysis: Develop embedding‑based search tools and active learning workflows to identify critical scenarios.
• Monitor Production Performance: Build dashboards to monitor model health, data drift, system performance; identify regressions and support services.
• Learn and Apply Best Practices: Follow software engineering standards, CI/CD, unit testing; participate in code reviews and documentation.
• Collaborate Across Teams: Work with senior and fellow ML engineers to translate prototypes into scalable solutions.

• BS or MS in Computer Science, Machine Learning or related field.
• Hands‑on experience with PyTorch (preferred) or Tensor Flow/JAX.
• Proficiency in Python and ability to write clean, modular code.
• Knowledge of version control, unit testing, basic software patterns.
• Experience with large datasets, SQL, Pandas, Num Py.
• A solid grasp of the full ML lifecycle from data cleaning to deployment.
• Proactive learner, eager to grow in high‑stakes engineering.

• MS/PhD in relevant field.
• Experience with agentic systems, autonomous reasoning, chain‑of‑thought models, or LLM‑based planning.
• Background in autonomous driving, robotics, or real‑time decision‑making.
• Familiarity with multimodal learning, sensor fusion, embodied AI.
• Experience building active learning loops.
• Experience with ML‑based data mining, contrastive learning.
• Knowledge of model serving (TF Serving, Triton, Torch Serve) and MLOps platforms.
• Publication in top‑tier conferences.

Boston, Las Vegas, Pittsburgh, or Remote U.S. Flexible hybrid or fully remote.

Estimated base salary range: $144,000 — $192,000 USD. Additional compensation may include bonuses and equity. Benefits include medical, dental, vision, 401(k) with match, health savings account, life insurance, pet insurance, and more.

Motional AD Inc. is an EOE. We celebrate diversity and are committed to an inclusive environment. All newly‑hired employees are queried through the E-Verify system to verify eligibility.