Machine Learning Engineer II

Essential Responsibilities

• Work closely with senior technologists to train, optimize and evaluate vehicle-oriented Machine Learning models
• Work cross functionally with Perception, Behavior, Integration, Test and Data teams to ensure the highest quality in model performance and deployment

Skills and Abilities

Success in this role typically requires the following competencies:

• Experience and interest in one of the following specific domains:
  • ML Runtime or Training Optimization
  • Training Infrastructure
  • Performance evaluation
  • Data Centric Machine Learning
• Functional proficiency with Software concepts such as memory management, threading, databases and networking
• Familiarity with common Perception, Planning and Foundation model concepts in Autonomous Driving.

Qualifications and Experience

Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience:

Required

• Bachelor’s or Master’s degree in Robotics, Computer Science, Computer Engineering, or a related field with strong mathematical and engineering foundations.
• A minimum of 2 years training, optimizing and/or evaluating ML Models in a commercial environment.
• Proficiency in C/C++/Python/PyTorch and experience in Linux environments.

Desirable

• Experience optimizing ML models for resource-constrained hardware
• Experience with CUDA and GPU processing techniques
• Proficiency with hard example mining, active learning or dataset composition techniques
• Experience calculating metrics for and evaluating autonomous vehicle models
• Experience building training and evaluation pipelines for large data (>100TB) or large model (>100GB) applications

Physical Requirements

• Standard office working conditions which includes but is not limited to:
  • Prolonged sitting
  • Prolonged standing
  • Prolonged computer use