Lead Data Scientist

Overview

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 Multi-Policy Decision Making (MPDM) technology that reimagines the way AVs think. Our vehicles 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. 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.

Lead Data Scientist

As a Lead Data Scientist, you will be a critical contributor to the design, development, and deployment of advanced machine learning solutions. Your expertise will be instrumental in leveraging large-scale, multi-modal video and sensor streams to create automated, scalable systems that extract meaningful insights. This role requires a hands-on approach to the entire ML lifecycle, from problem analysis to building and product ionizing robust, scalable models, with a primary focus on making unstructured video data accessible and searchable.

• Develop video understanding models, from design and implementation to fine-tuning
• Collaborate with engineering teams to integrate machine learning models into production systems, ensuring scalability, low latency, and reliability for real-time and offline processing.
• 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.
• Communicate complex analytical findings and model performance metrics to both technical and non-technical stakeholders through clear visualizations and presentations.
• Write clean, efficient, and well-documented Python code, adhering to best practices for data science development in a production environment.

• Expertise in deep 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.
• Proven ability to build and product ionize embedding-based models and large-scale systems.
• Expert-level programming skills in Python with extensive use of modern deep learning frameworks like Tensor Flow or PyTorch.
• Experience with distributed computing frameworks such as PySpark or Dask for processing large-scale video datasets.
• 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
• Experience with Vision-Language Models (VLMs) and fine-tuning large-scale foundational models for multi-modal tasks is a strong plus.

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.
• Demonstrated experience in building and deploying production-level machine learning systems from conception to delivery.
• Proven track record of building and fine-tuning deep learning models
• Direct experience working with multi-modal datasets, including video, image, and sensor data.
• Extensive experience with programming languages such as Python and distributed computing frameworks.

Desirable

• Demonstrated ability to mentor and support junior engineers
• Experience with Vision-Language Models (VLMs) or other large-scale foundational models.
• Background in robotics, autonomous systems, or natural language processing.
• Experience with MLOps platforms and cloud…