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2021 Summer PhD Backend Software Engineer Intern

Location San Francisco, United States
Posted 20-March-2021
Description
About the Role

Ubers fulfillment and product intelligence platforms are looking for Ph.D. student interns for summer of 2021. We seek candidates with a background in databases, distributed systems and infrastructure.

You will work closely with members of the group on building or extending tools that improve Ubers fulfillment and experimentation systems. These are systems that are critical for the realtime operation of every trip at Uber.

Most intern projects also have external visibility via open-source, blog posts, publications, or talks.

About the Fulfillment Team

Designs, builds, and operates the always-on platform for Uber to ensure that every trip is a magical one from the time you request a ride to the time you complete a ride. The team provides the foundation and business models to enable transportation of people & things from origin to destination.

Work on services that handle a significant % of critical inbound traffic to Uber.
Design systems and features with resilience in mind. Some top of mind concerns include network, location or device failures.Handle challenges around consistency and distributed state management at scale across a number of services.Work with partner teams to model new features and customer experiences into a fulfillment platform with a focus on extensibility and clean design.

Sample projects:
An auto-scaling system for a realtime database layer that saves 10s of millions of dollars a year.Build an end to end streaming upload solution that powers all media upload across all uber projects.Develop a ML model & user cohort to analyze uber interaction with Uber based on log analysis.Build a state machine analysis tool that provides visibility into the fulfillment states in realtime for user debugging at scale.

About the Product Intelligence Team

Designs, builds, and operates the experimentation and metrics platform Uber uses to make every product decision at the company. This full stack data team builds mobile SDKs, at scale backends (500k+ QPS), large scale data pipelines and systems (1.5 Petabyte data stores), statistics engines and analytics tools, front-ends, and lambda/kappa streaming architectures that power both human and machine decision making within the company. Work on applied science problems at Uber scale.

Sample projects:

Build automated backfill tools for lambda, kappa, and kappa+ architectures;Build query optimizers for efficient computation in Ubers metric registry;Optimize near-real time streaming pipelines for business critical ML Features and metrics;Design data science libraries with new statistical techniques for experiment evaluation;Extend tier-0 at scale services to optimize away tight latency budgets and increase reliability.

What Youll Do
Work with your mentor closely to scope a project, define the problem, and develop and prototype the solutionDevelop creative and novel solutions to deep technical problems and implement those solutionsConnect with engineers company-wide to understand the use cases and feasibility of your work, and collaborate on productizing your workWork as appropriate on open sourcing and publishing your work
Basic Qualifications
Currently enrolled in a Ph.D. program studying distributed systems, database designs and machine learning.
Preferred Qualifications
Passionate about writing clean, efficient, and well-tested codeAbility to communicate effectively with both technical and business stakeholders

 
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