Machine Learning Engineer – Collision Avoidance System
| Company | Zoox |
|---|---|
| Location | San Mateo, CA, USA |
| Salary | $204000 – $256000 |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s, PhD |
| Experience Level | Senior, Expert or higher |
Requirements
- BS, MS, or PhD degree in computer science or related field
- Experience with training and deploying Deep Learning models
- Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
- Fluency in C++
- Extensive experience with programming and algorithm design
- Strong mathematics skills
- 8+ years of experience in a related field
Responsibilities
- You will lead a team of deep learning engineers leveraging technical and managerial skills to deliver high-impact results
- You will set the short and long term technical direction for the team and collaborate on the broader company-wide directions
- You will coordinate cross-functional initiatives with other teams across CAS, Systems Engineering, QA, and more
- You will develop new algorithms that consume raw sensor data input to detect dynamic entities in the world
- You will leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field
- You will engineer software that runs on-vehicle to efficiently execute our algorithms in real time
- You will develop metrics and tools to analyze errors and understand improvements of our systems
- You will collaborate with engineers on the other parts of CAS Perception, CAS Verification & Validation, CAS Planner, and the Main AI teams to solve the overall Autonomous Driving problem in complex urban environments
Preferred Qualifications
- Conference or Journal publications in Machine Learning or Robotics related venues
- Prior experience with Prediction and/or autonomous vehicles in general
- Fluency in Python