Lead Data Scientist (Machine Learning)

• Work independently with cross functional teams to develop software and system requirements
• Design, implement, and deploy state-of-the-art machine learning models
• Monitor the performance of the ML models and drive continuous improvement
• Lead team code quality activities including design and code reviews
• Communicate complex analytical findings and model performance metrics to both technical and non-technical stakeholders through clear visualizations and presentations
• Provide technical guidance to team members

Benefits

• Onsite, Hybrid, and Remote Work Options- If you’re excited about this role but your previous experience doesn’t align perfectly with every qualification, we encourage you to apply anyway! You may be the perfect candidate for this or another role at May
• 10+ years of hands-on experience as a Data Scientist or ML Engineer with a strong focus on algorithmic design and deep learning
• Awareness of the latest advancements in the field, with the ability to translate innovative concepts into practical solutions for May
• Expert-level programming skills in Python with extensive use of modern deep learning frameworks like TensorFlow or PyTorch
• Solid understanding of ML deployment lifecycle, MLOps practices, and cloud computing platforms (e.g., AWS, GCP)
• Experience with classifying driving maneuvers and traffic interactions using machine learning methods
• Background in robotics or autonomous systems
• Strong understanding of data labeling best practices, label consistency, and performance metrics specifically relevant to large-scale auto-tagging accuracy and dataset curation
• Ability to provide individual and team mentorship, including technical leadership for complex projects
• Excellent problem-solving skills with a meticulous approach to model architecture and optimization
• Demonstrated experience in building and deploying production-level machine learning systems from conception to delivery
• Demonstrated expertise in databases for data extraction, transformation, and analysis
• 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)
• Expertise in PySpark/Apache Spark for handling large-scale data processing
• Ability to build and productionize machine learning models and large-scale systems
• Expertise in deep learning, with hands-on experience in the design, training, and evaluation of a wide range of algorithms
• B.S, M.S. or Ph.D. Degree in Engineering, Data Science, Computer Science, Math, or a related quantitative field
• Prior experience in mentoring and supporting junior engineers
• Experience with multi-modal deep learning models, transformers, visual learning models etc