Lead Machine Learning Engineer

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.

• Standard office working conditions which includes but is not limited to:
• Prolonged sitting
• Prolonged standing
• Prolonged computer use
• Travel required? -  Low: 5%-10%

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.