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Software Engineer - Deep Learning Platform (Seattle)

Backend, Engineering
in Seattle, Washington

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.

About the Role

Uber is on the lookout for top-notch software engineers to join our Deep Learning Platform team in Seattle. 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.

The Deep Learning Platform team in Seattle works on software and services that democratizes and empowers teams in Uber to use the technology. You will join a team of strong software and systems engineers, executing in a fast paced environment. The Deep Learning Platform team is part of Michelangelo. For more information on the Michelangelo team as a whole, see recent blog posts:

What You'll Do

  • Design and deliver software and tools as part of our state-of-the-art Deep Learning platform.
  • Systems architecture design, including management of upstream and downstream dependencies.
  • Provide technical leadership, influence and partner with fellow engineers to architect, design and build infrastructure that can stand the test of scale and availability, while reducing operational overhead.
  • 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.
  • Collaborate with platform, product and security engineering teams, and enable successful use of infrastructure and foundational services.

Basic Qualifications

  • BS or MS in Computer Science or a related technical field, or equivalent experience.
  • Sound understanding of computer architecture and CS fundamentals.
  • Proficient in one of the following programming languages: Java, Go, Python, C/C++.
  • Good working knowledge of networking, Linux, Docker, databases, Hadoop, Hive, Spark.

Preferred Qualifications

  • 5+ years of experience of systems software engineering.
  • Experience in building and managing distributed systems and high-throughput services.
  • Systematic problem solving approach and knowledge of algorithms, data structures and complexity analysis.
  • Grit, drive and a strong feeling of ownership coupled with collaboration and leadership.
  • Experienced production user of Deep Learning frameworks such as Tensorflow, PyTorch, Keras, etc.
  • Power-user Linux knowledge and willingness to explore Linux internals.
  • Experience in managing dependencies in data science packages.
  • Experience in high performance computing.

At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 10,000 cities around the world.

We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let's move the world forward, together.

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.