Staff Software Engineer: Large-Scale ML & Systems Leader

Uber; Sunnyvale (CA); On-site; USD 265,000 - 284,000; Full time

Benefits offered by this job

Bonus program

Equity

Benefits

Job summary

Uber is seeking a Staff Software Engineer to anchor large-scale systems, from orchestration platforms to globally deployed services. You will shape architecture, own outcomes, and help scale a high-performance foundation that powers the world’s rides and deliveries.

Design, develop, and test software across the stack; set long-term direction for retrieval, ranking, and query understanding; explore generative AI and deep learning to create novel solutions while mentoring ML engineers and

Qualifications

• Bachelor's degree in Statistics, Economics, Mathematics, Computer Science, Machine Learning, OR related field, plus 5 years of progressive experience.
• 5 years of experience in developing and deploying machine learning models in production environments.
• Experience in ML system architecture and design; ML algorithms, modeling, and modern deep learning approaches.

Responsibilities

• Design, develop, and test software applications across the stack.
• Set long-term technical direction for retrieval, ranking, and query understanding.
• Evaluate emerging technologies like generative AI and deep learning for novel solutions.
• Provide expert mentorship to ML engineers and scientists.
• Foster cross-functional collaboration and engineering excellence.

Skills

Large-scale ML systems

Python

Java

MLOps

Spark

Hadoop

SQL

Education

Bachelor's degree in Statistics, Economics, Mathematics, Computer Science, Machine Learning, Operations Research, or related field

Tools

Spark

Hadoop

Job description

Uber is seeking a Staff Software Engineer to anchor large-scale systems, from orchestration platforms to globally deployed services. You will shape architecture, own outcomes, and help scale a high-performance foundation that powers the world’s rides and deliveries.

Design, develop, and test software across the stack; set long-term direction for retrieval, ranking, and query understanding; explore generative AI and deep learning to create novel solutions while mentoring ML engineers and