Senior Staff Machine Learning Engineer
Perception
Confirmed live in the last 24 hours
Aurora Innovation

1,001-5,000 employees

Self-driving technology provider for various vehicles
Company Overview
Aurora stands out as a leading company in the autonomous driving industry, with its Aurora Driver system designed to operate a variety of vehicle types, demonstrating its versatility and broad applicability. The company's commitment to safety and efficiency is evident in its use of advanced sensor fusion and proprietary computing, enabling the system to understand and navigate complex environments. Furthermore, Aurora's partnerships with industry leaders across the transportation ecosystem, such as Toyota, FedEx, and Uber, underscore its industry leadership and potential for large-scale impact.
Data & Analytics
Hardware
Industrial & Manufacturing

Company Stage

N/A

Total Funding

$5.4B

Founded

2017

Headquarters

Mountain View, California

Growth & Insights
Headcount

6 month growth

4%

1 year growth

2%

2 year growth

21%
Locations
Mountain View, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
Tensorflow
Data Structures & Algorithms
Pytorch
Computer Vision
CategoriesNew
AI & Machine Learning
Applied Machine Learning
Deep Learning
Computer Vision
Requirements
  • Excellent software engineering skills in Python and/or C++
  • Extensive exp in any deep learning framework, such as PyTorch, JAX, TensorFlow
  • Extensive exp in Computer Vision, Machine Learning, Deep Learning, or other relevant areas of Artificial Intelligence (e.g., as evidenced by industry experience, publication record)
Responsibilities
  • Collaborate with other members of the Perception autonomy team to improve/ideate and implement perception algorithms that power the Aurora Driver
  • Serve as a technical expert for the team on at least one area related to machine learning, with particular focus on computer vision, recursive state estimation, structured prediction, optimization, and others
  • Research and develop state-of-the art deep learning/machine learning models to improve our perception solutions under challenging and diverse scenarios (e.g., on highways and city streets, long-range and multi-sensor object detection, detection under degraded sensors, etc.)
  • Design, prototype and evaluate machine learning algorithms and DNN architectures for detection of traffic actors, their action recognition, and semantic understanding of various traffic scenes that the Aurora Driver encounters
  • Integrate, test, and deploy production-ready solutions into the production code that powers the Aurora Driver.