May Mobility
Machine Learning Engineer II - Autonomous Driving Training Infrastructure
$160K–$210K
USA - Remote +1 · Remote · Full-time · Posted Jun 5, 2026
- Location
- USA - Remote
Ann Arbor, Michigan, United States - Experience
- A minimum of 2 years building ML-oriented infrastructure, platforms, or distributed systems in production.
- Education
- Bachelor’s or Master’s degree in Robotics, Computer Science or a related field with strong mathematical and engineering foundations.
About the job
Designs and operates scalable data, training, and evaluation infrastructure to move autonomous-driving machine learning models from concept to commercial deployment.
What you'll do
- Own the transition of autonomous-driving ML models from concept to commercial scale.
- Architect and operate data, training, and evaluation pipelines across cloud and cluster environments.
- Design and maintain data and metadata stores for training and evaluation workflows.
What they ask for
- Bachelor’s or Master’s degree in Robotics, Computer Science, or a related field with strong mathematical and engineering foundations.
- At least 2 years building ML-oriented infrastructure, platforms, or distributed systems in production.
- Proficiency in C++, Python, and PyTorch, with experience in Linux environments.
- Familiarity with basic machine learning concepts, including training loops, operators, and architectures.
Nice to have
- Familiarity with autonomous-driving Perception and Planning concepts.
- Experience with Go or Rust, ML orchestration and experiment tooling, distributed training frameworks, or data pipeline and storage technologies.
Pay
$160,000 — $210,000 USD (base salary)
Tools
C++, Python, PyTorch, Linux, Go, Rust, Ray, Kubeflow
AI focus
Build and scale infrastructure and pipelines for training and evaluating autonomous-driving ML models.
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