Lead Data Scientist (ML)

May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. Based in Ann Arbor, Michigan, May develops and deploys autonomous vehicles (AVs) powered by our innovative Multi-Policy Decision Making (MPDM) technology that literally reimagines the way AVs think. 

Our vehicles do more than just drive themselves - they provide value to communities, bridge public transit gaps and move people where they need to go safely, easily and with a lot more fun. We’re building the world’s best autonomy system to reimagine transit by minimizing congestion, expanding access and encouraging better land use in order to foster more green, vibrant and livable spaces. Since our founding in 2017, we’ve given more than 300,000 autonomy-enabled rides to real people around the globe. And we’re just getting started. We’re hiring people who share our passion for building the future, today, solving real-world problems and seeing the impact of their work. Join us.

May Mobility is experiencing a period of significant growth as we expand our autonomous shuttle and mobility services nationwide. We are seeking talented data scientists and machine learning engineers to develop automated methods for contextualizing data collected by our autonomous vehicles. This will enable us to generate valuable insights from our data, making it easily searchable for triaging issues, creating test sets, and building datasets for autonomy improvements. Join us and make a crucial impact on our development and business decisions!

Responsibilities

• 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.

Skills

Success in this role typically requires the following competencies:

• Expertise in deep learning, with hands-on experience in the design, training, and evaluation of a wide range of algorithms.
• Ability to build and productionize machine learning models and large-scale systems.
• 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.
• Ability to provide individual and team mentorship, including technical leadership for complex projects.
• Strong understanding of data labeling best practices, label consistency, and performance metrics specifically relevant to large-scale auto-tagging accuracy and dataset curation.

Qualifications and Experience

Required

• B.S, M.S. or Ph.D. Degree in Engineering, Data Science, Computer Science, Math, or a related quantitative field.
• 10+ years of hands-on experience as a Data Scientist or ML Engineer with a strong focus on algorithmic design and deep learning.
• 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.
• 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).
• Demonstrated expertise in databases for data extraction, transformation, and analysis.
• Prior experience in mentoring and supporting junior engineers.

Desirable

• Background in robotics or autonomous systems.
• Experience with multi-modal deep learning models, transformers, visual learning models etc.
• Experience with classifying driving maneuvers and traffic interactions using machine learning methods.
• Solid understanding of ML deployment lifecycle, MLOps practices, and cloud computing platforms (e.g., AWS, GCP).
• Expertise in PySpark/Apache Spark for handling large-scale data processing.

Benefits and Perks

• 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