Lead ML Engineer - Autonomous Driving (Remote, USA)

May Mobility, Inc.

Northern (KY)

Hybrid

USD 220,000 - 270,000

Full time

17 hours ago
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Benefits offered by this job

Healthcare package
Retirement plan
Parental leave
Flexible vacation

Job summary

May Mobility, Inc. is seeking Machine Learning Leaders to advance autonomous vehicle ML capabilities. You will design and evaluate models for AV and simulation stacks, exploring VLA and Foundation models for commercial-scale problems, while leading small teams of engineers.

You will define data balance and training practices to enable efficient petabyte-scale training. The role emphasizes strong Python/PyTorch skills, experience with large multimodal datasets, and deployment to edge hardware in

Qualifications

  • 4+ years in commercial robotics or related industry.
  • 1 year mentoring ML Engineers in a corporate or lab setting.
  • Strong Python/PyTorch experience in Linux environments.
  • Practical experience handling long-tail failures in ML.

Responsibilities

  • Design, train and evaluate state-of-the-art models for AV and ML Platform.
  • Leverage End-to-End driving, VLA and Foundation models for scale.
  • Lead small cross-functional teams of 2-3 engineers.
  • Define data balance and training/evaluation practices at petabyte scale.

Skills

VLA/World Models
Large multi-modal datasets
Team leadership
Python/PyTorch
C/C++/CUDA
Edge deployment
LiDAR/Camera/Radar

Education

Master’s degree (Robotics/CS/CE)
PhD or published research

Tools

Python
PyTorch
Linux
CUDA

Job description

May Mobility, Inc. is seeking Machine Learning Leaders to advance autonomous vehicle ML capabilities. You will design and evaluate models for AV and simulation stacks, exploring VLA and Foundation models for commercial-scale problems, while leading small teams of engineers.

You will define data balance and training practices to enable efficient petabyte-scale training. The role emphasizes strong Python/PyTorch skills, experience with large multimodal datasets, and deployment to edge hardware in

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