Sr Staff Engineer - Programming Systems

    • Uber Corporate
  • San Francisco, CA
  • Posted 50 days ago | Updated 4 hours ago


On Site
USD 252,000.00 - 280,000.00 per year
Full Time


Program evaluation
Generative Artificial Intelligence (AI)
Open source
Dynamic testing
Code refactoring
Computer science
Software development
Software engineering
Profit and loss
Concurrent computing

Job Details

About the Role

At Uber's Programming Systems Group (PSG), we develop programming language (PL) techniques to enhance developer productivity and make our systems efficient and reliable. We leverage novel work on compiler optimizations, static and dynamic program analysis, performance tooling and optimizations, and generative AI as applied to developer tooling.

PSG members focus on solving real problems at scale for Uber developers across all languages and platforms. The team has a track record of innovative PL research (publications in PLDI, OOPSLA, ICSE, FSE, ASPLOS, CGO) and cutting-edge industry-standard open-source tools.

What You'll do

You will help delight our engineering teams, and redefine the standard for developer tooling through innovative work in compilers and program analysis. This includes (but is not limited to):
  • Static analyzers / pluggable type systems
  • Dynamic analysis tools (e.g., for concurrency bug detection)
  • GenAI-powered and rules-based program repair and code refactoring
  • Profile-guided compiler optimizations
  • Performance measurement, analysis, and optimization tools
---- Basic Qualifications ----
  • Ph.D. in Computer Science or a related discipline, or equivalent experience.
  • 6+ years of professional software development experience, including some experience as a tech lead for multiple areas
  • Knowledge of different compilation steps (and ability to troubleshoot) in languages such as Go, C, C++, or Java
Note that up to 3 years of the total required software engineering experience may have been gained through education and full-time work experience, additional training, coursework, research, or similar (OR some combination of these). The years of specialized experience are not necessarily in addition to the years of Education & full-time work experience indicated.

---- Preferred Qualifications ----
  • Experience leveraging Generative AI and Machine Learning infrastructure to concretely impact engineering productivity
  • Experience building and iterating on code review (phabricator, GitHub), automation test infrastructure (unit, integration, E2E), and build systems (Bazel / buck)
  • Experience working with teams spanning geographic locations and time-zones
  • Linux and Kubernetes system knowledge
For San Francisco, CA-based roles: The base salary range for this role is USD$252,000 per year - USD$280,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$252,000 per year - USD$280,000 per year.

For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link .

Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing .

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.