Job description

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 500,000 autonomous 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. We are seeking Machine Learning Leaders in the Autonomous Vehicle domain. As part of our team, you will play a critical role in enhancing May’s Machine Learning capabilities both on and off the vehicle, in a commercial large-scale environment with high standards of quality. Essential Responsibilities Design, train and evaluate state of the art models for May’s autonomous driving, simulation and ML Platform stack. Leverage emerging techniques in the End-to-End driving, Vision Language Action (VLA), World or Foundation model domains to solve commercial-scale problems. Lead small teams of cross functional Engineers beyond the state of the art. Define data balance, training experiment and evaluation practices to train efficiently at petabyte scale. Skills and Abilities Success in this role typically requires the following competencies: Direct experience architecting & training VLA, MMLM, or Generative World Models for commercial-scale applications Experience composing, processing and characterizing large (>100TB) multi-modal datasets Experience analyzing and addressing long-tail failure cases in large models Experience leading teams of 2-3 Engineers and communicating technical details to interdisciplinary leadership. Qualifications and Experience Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience: Required Extensive practical experience in one of the following domains: Vision Language Action Models Generative World Models Foundation Models in Robotics Data Centric AI A minimum of 4 years of industry experience working on commercial robotics systems. A minimum of 1 year mentoring ML Engineers in a commercial or lab environment. Master’s degree in Robotics, Computer Science, or Computer Engineering, or a field that requires a strong mathematical and/or engineering foundation. Practical experience handling the “Long Tail” problem in Machine Learning. Strong programming skills in Python/PyTorch in a Linux environment. Functional understanding of LiDAR, Camera and Radar processing techniques. Desirable PhD and/or published research in the described specialty domains. Familiar with common post-training techniques. Experience deploying models to resource constrained and edge hardware Functional understanding of C/C++/CUDA memory and threading models. Physical Requirements Standard office working conditions which includes but is not limited to: Prolonged sitting Prolonged standing Prolonged computer use Travel required? - Low: 5%-10% 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 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 Don’t meet every single requirement? Studies have shown that women and/or people of color are less likely to apply to a job unless they meet every qualification. At May Mobility, we’re committed to building a diverse, inclusive, and authentic workforce, so 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. Want to learn more about our culture & benefits? Check out our website ! May Mobility is an equal opportunity employer. All applicants for employment will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity or expression, veteran status, genetics or any other legally protected basis. Below, you have the opportunity to share your preferred gender pronouns, gender, ethnicity, and veteran status with May Mobility to help us identify areas of improvement in our hiring and recruitment processes. Completion of these questions is entirely voluntary. Any information you choose to provide will be kept confidential, and will not impact the hiring decision in any way. If you believe that you will need any type of accommodation, please let us know. Note to Recruitment Agencies: May Mobility does not accept unsolicited agency resumes. Furthermore, May Mobility does not pay placement fees for candidates submitted by any agency other than its approved partners. Salary Range $220,000 — $270,000 USD May Mobility uses automated tools to support — but not replace — human judgment in our recruiting process, to find out more please click here

Requirements

Must-haves

Design, train and evaluate state of the art models for May’s autonomous driving, simulation and ML Platform stack.
Leverage emerging techniques in the End-to-End driving, Vision Language Action (VLA), World or Foundation model domains to solve commercial-scale problems.
Lead small teams of cross functional Engineers beyond the state of the art.
Define data balance, training experiment and evaluation practices to train efficiently at petabyte scale.
Skills and Abilities
Success in this role typically requires the following competencies:
Direct experience architecting & training VLA, MMLM, or Generative World Models for commercial-scale applications
Experience composing, processing and characterizing large (>100TB) multi-modal datasets
Experience analyzing and addressing long-tail failure cases in large models
Experience leading teams of 2-3 Engineers and communicating technical details to interdisciplinary leadership.
Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience:
Extensive practical experience in one of the following domains:
Vision Language Action Models
Generative World Models
Foundation Models in Robotics
Data Centric AI
A minimum of 4 years of industry experience working on commercial robotics systems.
A minimum of 1 year mentoring ML Engineers in a commercial or lab environment.
Master’s degree in Robotics, Computer Science, or Computer Engineering, or a field that requires a strong mathematical and/or engineering foundation.
Practical experience handling the “Long Tail” problem in Machine Learning.
Strong programming skills in Python/PyTorch in a Linux environment.
Functional understanding of LiDAR, Camera and Radar processing techniques.
PhD and/or published research in the described specialty domains.
Familiar with common post-training techniques.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

gomachine learningmlaipython

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

Parental Leave

Wellness