> Markdown version of [/jobs/ext/4617077-staff-software-engineer-continuous-learning](https://www.wearedevelopers.com/jobs/ext/4617077-staff-software-engineer-continuous-learning). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Software Engineer, Continuous Learning - **Company:** Aurora Corporation - **Location:** San Francisco, CA, United States - **Salary:** $189,000.0 - $303,000.0 - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Computer Vision, Microsoft Azure, C++ (Programming Language), Cloud Computing, Databases, Shard (Database Architecture), Software Design Patterns, Distributed Systems, Protocol Buffers, Hadoop Distributed File System, Python (Programming Language), NoSQL, Software Engineering, SQL Databases, Parquet, Google Cloud, Load Balancing, Pytorch, System Availability, Large Language Models, Deep Learning, Caching, Gpu Programming, Information Technology - **Published:** November 7, 2026 - **Apply:** https://www.juju.com/job/28_25303_693e4f43e6cba0f39a06da6b153b017d ## About the Role * BS in Computer Science, or a related field * Excellent Python, Proficient 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 computer vision, LLMs, or deep learning for other applications, * Excellent C++ programming and software design skills * Distributed System design patterns (high availability, scaling, load balancing, caching, sharding etc.) * PyTorch and GPU programming experience ## Description * Improve our dataset quality by establishing semi-automated evaluation mechanisms leveraging state of the art models as well as RLHF techniques * Expand our foundation model approach for sourcing interesting events to millions of miles * Own model training and inference pipelines for all core Autonomy models * Collaborate across teams and functions (product, program, operations, data science) to drive projects from inception to delivery