Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We’re searching for a Software Engineer - Autonomy Data: Continuous Learning.

In this role, you will

• Support feature development for our labeling applications and data access
• Collaborate with autonomy engineers to improve the quality and composition of our datasets
• Leverage production best practices to guarantee a reliable platform for labeling operations, model training, and evaluation workflows
• Optimize data pipelines handling sensor data from millions of miles of on-road driving and richly-structured label data
• Collaborate across teams and functions (Product, Operations, Data Science) to drive projects from inception to delivery

Required Qualifications

• BS in Computer Science, or a related field
• Excellent Python / Basic C programming and software design skills
• Experience with storage and database management systems (e.g., one of SQL, no-SQL, protobuf, parquet, HDFS)
• Experience working in a cloud environment (e.g., AWS, GCP, Azure, etc)
• Knowledge and experience in at least one of Perception, 3D geometry, autonomous driving, 3D computer vision, robotics, mapping, 3D labeling

Desirable Qualifications 

• Excellent C programming and software design skills
• Distributed System design patterns (high availability, scaling, load balancing, caching, sharding etc.)

The base salary range for this position is $144,000-$216,000 per year. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

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#Mid-Senior