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Staff Software Engineer - AI/ML

Machine Learning, Engineering
in Sunnyvale, California

About the Role

Uber AI’s mission is to optimize and innovate Uber’s products and business using machine learning and AI. The group consists of Uber's machine learning platform team which enables machine learning at scale, AI building blocks which enable product teams to build unique experiences and engagements with product teams on their business problems.

The group consists of machine learning engineers, mobile engineers, backend engineers and research scientists and engineers.

Uber is on the lookout for top-notch software engineers to join our Michelangelo Machine Learning Platform team in the California Bay Area. This role involves building and managing robust distributed systems, and solving infrastructure challenges to empower Uber's product engineering and data science teams with the latest technologies in Artificial Intelligence. You will join a team of strong software and systems engineers, executing in a fast paced environment.

Checkout some of our recent blogs:

From Predictive to Generative – How Michelangelo Accelerates Uber’s AI Journey:

Scaling AI/ML Infrastructure at Uber:

What the Candidate Will Do ----

  • Envision, design, and deliver software and tools as part of state-of-the-art machine learning platform.
  • System architecture design, including management of upstream and downstream dependencies.
  • Drive efficiencies in systems and processes through automation: capacity planning, configuration management, performance tuning, monitoring, and root cause analysis.
  • Participate in periodic on-call rotations and be available for critical issues.

---- Basic Qualifications ----

  • BS or MS in Computer Science or a related technical discipline, or equivalent experience.
  • 7+ years of software engineering experience
  • Experience in systems software engineering. Sound understanding of computer architecture and CS fundamentals.
  • Proficient in one of the following programming languages: Java, Scala, Go, Python, C/C++.

---- Preferred Qualifications ----

  • Systematic problem-solving approach and knowledge of algorithms, data structures, and complexity analysis.
  • Experience in building and managing distributed systems.
  • Grit, drive and a strong feeling of ownership coupled with teamwork.
  • Knowledge of big data analytics technologies such as Apache Spark, Hadoop, Hive, Presto.
  • Experience in developing machine learning platforms.
  • Experience designing analytic tooling

For Sunnyvale, CA-based roles: The base salary range for this role is USD$218,000 per year - USD$242,000 per year.

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 this form.

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.

See our Candidate Privacy Statement

Uber is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, Veteran Status, or any other characteristic protected by law.