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

As an engineer on the team, you will be building production systems to enable some of the most important parts of Uber's business - Fares, Matching, Safety, Pickup Experience, product recommendations. Our backend systems handle some of the highest data volumes at Uber, while needing to be reliable enough to support every single ride or eats experience. We power rich user experiences through personalized recommendations across Uber's products.

Uber is deeply rooted in the physical world -- our business requires a clear understanding of complicated real-world interactions and behaviors.

We create actionable insights that our partner product teams (Rider, Driver, Eats, Safety et al) use to improve customer and trip experiences using sensor data. We do this by researching new models and algorithms and building platforms to serve our insights to customers at Uber scale. We own the core location pipeline ("Blue-Dot") at Uber that drives decisions across systems like ETA, Traffic, Routing, Safety, Fares, Matching and more. We also work on creating foundational platforms that power user experiences through personalized recommendations across Uber's products and services.

What You'll Do

• Collect and process location data at trip scale
• Build backend systems & microservices that interact with other microservices behind our Matching, Fares, Map Matchings processes, product selection, Uber's Machine Learning stack.
• Use analytics identify issues, root cause problems and validate solutions that improve our systems
• Work closely with customer teams to productionize, integrate and validate systems end to end
• Build realtime streaming+RPC systems to process and service inferences for various downstream customers (Customer Obsession, fares etc)
• Work on data pipelines for machine learning use cases

Basic Qualifications

• 3+ years of professional industry experience
• Strong programming and debugging skills - joy of coding (we mainly use Go, Java & Python)
• Experience working with data at scale, including experience with some or all of the following: Cassandra, Hadoop, Hive, Kafka, Flink, Spark, SQL

Preferred Qualifications

• Experience with ML infrastructure and running models in production