Machine Learning Engineer II - Autonomous Driving Training Infrastructure

Required

• Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience:
• 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).
• Physical Requirements
• Standard office working conditions which includes but is not limited to: