Principal Machine Learning Engineer, Data Mining

Overview As a Machine Learning Engineer on Motional’s Data Mining team, you build ML-powered tools to uncover rare driving scenarios in multimodal data. You’ll work with state-of-the-art models to enable efficient data search, active learning, and dataset curation at scale. Your work helps improve model lifecycles, diagnostics, and production dashboards for real-time feedback. Join a mission-driven team shaping safer, more reliable autonomous driving through smarter data mining. Compensation / Benefitsmedical, dental, vision 401k with company matchhealth savings accountlife insurancepet insurancewellness programs Responsibilities Develop, train, and fine-tune multimodal ML models (vision, LiDAR) using supervised and self-supervised approaches Build scalable data preprocessing and augmentation pipelines; optimize model deployment with batch inference and quantization Create embedding-based search tools and active learning workflows for identifying critical driving scenarios Monitor production performance with dashboards; detect regressions and support data mining services Adhere to software engineering standards (version control, CI/CD, unit testing); contribute to documentation and code reviews Collaborate with senior engineers to translate prototypes into maintainable engineering solutions Key requirementsBS or MS in CS, ML, or related field Hands-on experience with PyTorch (preferred) or Tensor Flow/JAXProficiency in Python with clean, modular code Experience with version control, unit testing, and software design patterns Experience with large datasets; proficient in SQL and data libraries (Pandas, Num Py)Strong understanding of the ML lifecycle from data cleaning to deployment Proactive learner with ability to grow in a high-stakes engineering environmentproactive learnercollaborative mindsetopen to feedback and iterative improvement PyTorch (preferred) or Tensor Flow/JAXPython programmingSQL and data libraries (Pandas, Num Py)