Senior Engineer, Infrastructure

Summary

Join Motional AD Inc. as a Senior Engineer, Infrastructure and work on large-scale solutions for mining challenging driving scenarios to boost learned model performance in autonomous driving. Collaborate with ML infrastructure teams, contributing to continuous learning workflows. Research and develop methods for extracting uncertainty indicators to automatically mine challenging scenes and analyze model performance. Provide statistical insights on model uncertainty, generalization, and robustness. Conduct deep learning experiments, write technical reports, and guide junior researchers. This role may be performed remotely from any U.S. state. The salary range is $168,000 to $244,000 per year.

Requirements

• Bachelor’s degree in computer science, machine learning or a closely related technical field plus three years industry experience
• Three (3) years industry experience with Python, production-quality software development, applying solid software engineering principles such as configuration management, source control, build processes, code reviews, testing methodologies, app containerization, and continuous integration
• Three (3) years industry experience with core AWS services (S3, RDS, Athena, Redshift or EKS), and DBMS (PostgreSQL, MySQL, MongoDB or SQLlite)
• Two (2) years industry experience with autonomous vehicle (AV) sensors (Lidar, Camera & Radar), software, and algorithms
• Two (2) years industry experience writing SQL queries for data analysis purposes, data modeling and dashboarding for data analysis purposes (Looker or Redash)
• Two (2) years industry experience architecting and shipping high-performance & large-scale distributed systems deployed in real world robotics applications
• Two (2) years industry experience conducting system & software design, project management and practicing agile methodologies
• One (1) year industry experience building ML products AV applications such as Object Detection, Information Retrieval, or Image Segmentation

Responsibilities

• Work on large-scale solutions for mining challenging driving scenarios to boost learned model performance across various autonomous driving tasks
• Collaborate with ML (Machine Learning) infrastructure teams and contribute to workflows for continuous learning through iterative mining, error analysis, training and deployment
• Research and develop methods for extracting uncertainty and informativeness indicators to automatically mine for challenging scenes and analyze model performance
• Provide statistical depth and insights on model uncertainty, generalization and robustness
• Conduct deep learning experiments and write technical reports
• Provide guidance to junior researchers on research projects and design document reviews

Benefits

• Medical
• Dental
• Vision
• 401k with a company match
• Health saving accounts
• Life insurance
• Pet insurance