Machine Learning Engineer II - Autonomous Driving Training Infrastructure

Summary

May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. They are seeking ML-Oriented Software Engineers with experience in robotics applications to join their Autonomous Driving ML team, where the focus will be on designing and operating pipelines to improve their Autonomous Driving stack at scale.

Responsibilities

• Own the process to transition 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 the data and metadata stores that back our training and evaluation workflows

Skills

• Bachelor's or Master's degree in Robotics, Computer Science or a related field with strong mathematical and engineering foundations
• A minimum of 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 concepts in Machine Learning (training loops, basic operators and architectures)
• Familiarity with basic Perception and Planning concepts in Autonomous Driving
• Proficiency in Go or Rust
• Familiarity with ML orchestration and experiment tooling such as Ray, Kubeflow, Airflow, MLflow, or Weights & Biases
• Familiarity with distributed training frameworks (PyTorch DDP/FSDP, DeepSpeed)
• Familiarity with data pipeline and storage technologies (Spark, Parquet, object storage, feature/metadata stores)

Qualifications

Must Haves

• Bachelor's or Master's degree in Robotics, Computer Science or a related field with strong mathematical and engineering foundations
• A minimum of 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 concepts in Machine Learning (training loops, basic operators and architectures)

Nice to Haves

• Familiarity with basic Perception and Planning concepts in Autonomous Driving
• Proficiency in Go or Rust
• Familiarity with ML orchestration and experiment tooling such as Ray, Kubeflow, Airflow, MLflow, or Weights & Biases
• Familiarity with distributed training frameworks (PyTorch DDP/FSDP, DeepSpeed)
• Familiarity with data pipeline and storage technologies (Spark, Parquet, object storage, feature/metadata stores)

Benefits

• 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