Job Description
The role involves developing and improving datasets and models for autonomous driving technology, including leveraging state-of-the-art foundation models and reinforcement learning techniques, as well as managing training and inference pipelines to enhance the Aurora Driver system.
Key Responsibilities
- Improve dataset quality by establishing semi-automated evaluation mechanisms using state-of-the-art models and RLHF techniques
- Expand foundation model approaches for sourcing interesting events across millions of miles
- Own model training and inference pipelines for core Autonomy models
- Collaborate with cross-functional teams to drive projects from inception to delivery
Requirements
- Bachelor's degree in Computer Science or a related field.
- Excellent Python programming skills.
- Proficient C programming and software design skills.
- Experience with storage and database management systems such as SQL, no-SQL, protobuf, parquet, or HDFS.
- Experience working in a cloud environment such as AWS, GCP, or Azure.
- Knowledge and experience in at least one of the following areas: computer vision, large language models (LLMs), or deep learning for other applications.
- Own model training and inference pipelines for all core Autonomy models.
- Collaborate across teams and functions including product, program, operations, and data science to drive projects from inception to delivery.
Benefits & Perks
Compensation/salary range: 189,000-303,000 USD per year
Annual bonus
Equity compensation
Hybrid work environment with in-office presence at least 3 days per week
Benefits (unspecified, but includes standard employment benefits)
Ready to Apply?
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