ML-Driven Backend Engineer II — Scalable Systems

Uber; San Francisco (CA); On-site; USD 171,000 - 190,000; Full time

Benefits offered by this job

Bonus program

Equity award

401(k) plan

Benefits

Job summary

Uber is seeking a Software Engineer II (MLE) to architect scalable systems powering the delivery marketplace. You will design, develop, and maintain backend features with a focus on low latency and high reliability, while building ML models to boost delivery efficiency.

Join a global team focused on robust monitoring, cross-functional collaboration, and end-to-end ownership of the software lifecycle. In San Francisco, in-office presence is expected for collaboration and culture, with competitive

Qualifications

• 3+ years of professional software engineering experience backend/distributed systems/data engineering.
• Proficiency in Go, Java, Python, or C++.
• Experience applying ML, statistics, or optimization to large-scale problems.
• Experience with data modeling, query optimization, and translating customer problems into system design.
• Bachelor’s Degree in Computer Science, Engineering, or related field; testing and monitoring experience.

Responsibilities

• Design, develop, and maintain high-quality code for moderately complex features with dependencies.
• Develop and optimize ML models to improve delivery marketplace efficiency.
• Build and scale foundational infrastructure and data pipelines with long-term impact in mind.
• Own the software lifecycle end-to-end from design docs to production incident handling.
• Collaborate with Product, Data Science, and Ops to translate requirements into system designs.
• Provide quality code reviews, comprehensive tests, and performance improvements.

Skills

Go

Java

Python

C++

Education

Bachelor's Degree in Computer Science or Engineering

Job description

Uber is seeking a Software Engineer II (MLE) to architect scalable systems powering the delivery marketplace. You will design, develop, and maintain backend features with a focus on low latency and high reliability, while building ML models to boost delivery efficiency.

Join a global team focused on robust monitoring, cross-functional collaboration, and end-to-end ownership of the software lifecycle. In San Francisco, in-office presence is expected for collaboration and culture, with competitive