Senior ML Scientist
- Design, implement, and deploy state-of-the-art machine learning models for analyzing multimodal data to generate searchable metadata and facilitating downstream engineering workflows such as quick issue triaging.
- Research and implement novel techniques for sequential feature extraction, weak supervision, and self-supervised learning to efficiently handle long-tail events and continuously improve labeling data quality.
- Curate high-quality datasets by applying advanced data mining techniques to ensure model robustness, performance, and coverage.
- Establish and maintain frameworks for model validation and performance monitoring to drive continuous improvement.
- Expert proficiency in designing and implementing deep learning architectures for combining visual data with sequential or time-series data streams for offline analysis.
- Strong understanding of data labeling best practices, label consistency, and performance metrics specifically relevant to large-scale auto-tagging accuracy and dataset curation.
- Expertise in machine learning, with hands-on experience in the design, training, and evaluation of a wide range of algorithms.
- Awareness of the latest advancements in the field, with the ability to translate innovative concepts into practical solutions for May.
- Excellent problem-solving skills with a meticulous approach to model architecture and optimization.
- B.S, M.S. or Ph.D. Degree in Engineering, Data Science, Computer Science, Math, or a related quantitative field.
- 5+ years of hands-on experience as a Data Scientist or ML Engineer with a strong focus on algorithm design and machine learning.
- Experience working with multimodal data like visual data (images/video), structured perception and behavior outputs (e.g., agent tracks, vehicle state estimation, motion planner outputs).
- Expert-level programming skills in Python with extensive use of modern deep learning frameworks like TensorFlow or PyTorch.
- Demonstrated experience in building and deploying production-level machine learning systems from conception to delivery.
- Expertise in PySpark/Apache Spark for handling large-scale data processing.
- Background in robotics or autonomous systems.
- Experience working with multimodal data like visual data (images/video), structured perception and behavior outputs (e.g., agent tracks, vehicle state estimation, motion planner outputs).
- Solid understanding of ML deployment lifecycle, MLOps practices, and cloud computing platforms (e.g., AWS, GCP).
- Comprehensive healthcare suite including medical, dental, vision, life, and disability plans. Domestic partners who have been residing together at least one year are also eligible to participate.
- Health Savings and Flexible Spending Healthcare and Dependent Care Accounts available.
- Rich retirement benefits, including an immediately vested employer safe harbor match.
- Generous paid parental leave as well as a phased return to work.
- Flexible vacation policy in addition to paid company holidays.
- Total Wellness Program providing numerous resources for overall wellbeing
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