Lead Machine Learning Engineer (Autonomous Vehicles)

TL;DR

Lead Machine Learning Engineer (Robotics/AV): Designing and training state-of-the-art models for autonomous driving and simulation with an accent on Vision Language Action (VLA) and Generative World Models. Focus on solving commercial-scale long-tail failure cases and managing petabyte-scale multi-modal datasets.

Location: Ann Arbor, MI (Onsite)

Salary: $220,000–$270,000 USD

Company

hirify.global transforms cities through autonomous vehicle technology to create safer, greener, and more accessible urban transit.

What you will do

• Design, train, and evaluate SOTA models for autonomous driving, simulation, and the ML Platform stack.
• Leverage emerging techniques in End-to-End driving, VLA, and World/Foundation models to solve commercial-scale problems.
• Lead small teams of cross-functional engineers to push technical boundaries.
• Define data balance, training experiments, and evaluation practices at petabyte scale.

Requirements

• Must be able to work onsite in Ann Arbor, MI.
• Extensive practical experience in VLA, Generative World Models, Foundation Models in Robotics, or Data Centric AI.
• Minimum 4 years of industry experience working on commercial robotics systems.
• Minimum 1 year of experience mentoring ML Engineers in a commercial or lab environment.
• Master’s degree in Robotics, Computer Science, Computer Engineering, or a related mathematical field.
• Strong programming skills in Python/PyTorch within a Linux environment.

Nice to have

• PhD and/or published research in the specified specialty domains.
• Experience deploying models to resource-constrained edge hardware.
• Functional understanding of C/C++/CUDA memory and threading models.
• Familiarity with common post-training techniques.

Culture & Benefits

• Comprehensive healthcare suite including medical, dental, vision, life, and disability plans.
• Rich retirement benefits with an immediately vested employer safe harbor match.
• Generous paid parental leave and a phased return-to-work program.
• Flexible vacation policy in addition to paid company holidays.
• Total Wellness Program providing various resources for overall wellbeing.