Job Description

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 on the Machine Learning Data Engine: Labels Platform team. Our team is responsible for production services supporting high volume data labeling operations. We also provide data models and service interfacing supporting a variety of autonomy data consumers. Autonomy performance is directly dependent on data quality, selection, and volume. On this team you will have opportunities to work on projects that are mission-critical for the company. You will also have the opportunity to develop innovative industry-leading ML Ops solutions. Aurora is uniquely positioned to lead in this space due to its end-to-end data collection, labeling, model training and evaluation toolchain.
In this role, you will

• Apply production best practices to ensure platform reliability
• Feature development for new labeling applications
• Collaborate across teams and functions (product, program, operations, data science) to drive projects from inception to delivery
• Apply ML Ops best practices to design processes for improving data coverage and quality

Required Qualifications

• BS / MS / PhD degree in Computer Science or a related field
• For non-CS majors or BS candidates, strong software experience (4+ years in industry)
• 4+ years of expertise with production backend services (Cloud, Kubernetes, DevOps)
• Experience with C++ and Python

Desirable Qualifications

• Relevant domain knowledge: data annotation, autonomous driving, computer vision, robotics, mapping, numerical computing, 3D graphics
• Specific technology: AWS, Terraform, Bazel, Docker, Kubernetes, gRPC, SQL, Elasticsearch
• Supplementary programming languages: Golang, Typescript

The base salary range for this position is $126,000 - $201,000 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.
#LI-JL261
#Mid-Senior

Skills Required