Machine Learning Engineer - Rider Intelligence Team at Uber (South Bay)

| South Bay
Sorry, this job was removed at 5:43 a.m. (CST) on Friday, May 27, 2022
Find out who's hiring remotely in San Francisco, CA.
See all Remote Data + Analytics jobs in San Francisco, CA
Apply
By clicking Apply Now you agree to share your profile information with the hiring company.
On the Rides Engineering team, we write code that ignites opportunities for millions of people every day. We're focused on making Uber's core ridesharing products faster, safer, and more reliable by building scalable software solutions for riders and drivers on our platform.
About the Role
We have established a world-class Rider Intelligence engineering team to build critical machine learning solutions and frameworks to empower Uber's core Rider products. Our team's mission is to serve the ML needs of the entire Uber Rider organizations (> 200 people). In this role, you can have a significant impact on a wide range of Uber rider products and Uber consumers. We work on everything from enhancing rider growth and deepening engagement to growing Uber's footprint in the multi-modal trip marketplace. You will be on a super collaborative team designed to maximize your ability to deliver results. If you are motivated by building technically challenging machine learning and optimization problems in real-time and at scale, working on projects that impact every single Uber rider, knowing that every Uber rider sees and benefits from your work, and helping to drive Uber's top business metrics, then Rider Intelligence is the team for you at Uber!
What You'll Do
  • Build ML solutions to solve business needs across the Rider organization with over 200 engineers. Some of the types of projects you will work on:
  • Build a personalized real-time ride product recommendations engine to suggest the right products to the riders at the right time, to shift behavior, and improve the rider experience.
  • Supercharge Uber's rides and eats subscription upsells, target benefits incentives based on user interest and product usage, and impact Uber's business goals by improving acquisition and engagement.
  • Build shareable ML tools and frameworks to serve the ML needs of the entire Rider org
  • Ranking engine infrastructure to onboard personalized rider level recommendation ML use cases such as message targeting or benefits targeting, just to name a few!
Basic Qualifications
  • 7+ years of industry experience with a master or bachelor degree.*
  • 2+ years of experience building and productionizing innovative end-to-end Machine Learning systems.
  • Proven engineering and coding skills. Ability to write high-performance production quality code. Experience in Java, Go, Python and other equivalent languages is a plus.
  • Strong understanding of common families of models, feature engineering, feature selection, optimization algorithms
  • Proven track record to choose the right ML solutions to solve the problem within current constraints while having a clear vision of the next iterations and a good balance between exploration and exploitation of different techniques.
  • Experience with MapReduce, Spark and Hive on large datasets.
Preferred Qualifications
  • 5+ years of experience with a PhD in relevant fields (CS, EE, Math, Stats, Physics, etc.)*
  • Proven experience developing complex software systems scaling to millions of users with production quality deployment, monitoring and reliability.
  • Passion to use machine learning to empower Uber products.
  • Ability to go deep and build the most impactful solutions while also leading multiple directions across multiple teams and organizations to ensure the success of our mission.
  • Proven experience in simplifying/converting business problems into ML problems.

*Role initiatlly posted with incorrect required years of experience:
Basic Qualifications changed from 5+ years of required experience to 7+ years
Preferred Qualification changed from 3+ years of experience to 5+ years
Read Full Job Description
Apply Now
By clicking Apply Now you agree to share your profile information with the hiring company.

Technology we use

  • Engineering
  • Product
  • Sales & Marketing
    • C#Languages
    • C++Languages
    • GolangLanguages
    • JavaLanguages
    • JavascriptLanguages
    • KotlinLanguages
    • PerlLanguages
    • PHPLanguages
    • PythonLanguages
    • RLanguages
    • RubyLanguages
    • ScalaLanguages
    • SqlLanguages
    • SwiftLanguages
    • GoLanguages
    • ReactLibraries
    • ReduxLibraries
    • Twitter BootstrapLibraries
    • ASP.NETFrameworks
    • HadoopFrameworks
    • Node.jsFrameworks
    • SparkFrameworks
    • TensorFlowFrameworks
    • AccessDatabases
    • Microsoft SQL ServerDatabases
    • MySQLDatabases
    • Google AnalyticsAnalytics
    • FigmaDesign
    • PhotoshopDesign
    • FigmaDesign
    • AsanaManagement
    • ConfluenceManagement
    • JIRAManagement
    • WordpressCMS
    • DocuSignCRM
    • SalesforceCRM
    • SplashCRM
    • SendGridEmail
    • Adobe CampaignLead Gen

An Insider's view of Uber

What’s the vibe like in the office?

When I went into the office for my final interview with Uber, I had the same feeling that I did when I stepped onto my college’s campus for the first time: it just felt like the right fit. The office was high-paced but also relaxed and you could immediately tell that people were friends and genuinely enjoyed being there.

Paige Sammarco

Account Executive, Uber Eats

What kinds of technical challenges do you and your team face?

One of the big challenges today with experimentation is around guaranteeing correctness, especially for small changes to ensure confidence in results. Was that change the cause of new behavior? Did other experiments get in the way? It all comes down to how accurately you can detect small changes within consumer behavior.

Azarias Reda

Head of Uber's Experimentation API team

What makes someone successful on your team?

"It’s not just about the individual contributor. The most successful people are the ones learning from others. On my team, I make sure that everyone shares best practices and we foster a collaborative culture. So when you’re on a call, you’re never really alone. And that applies to everyone."

Ali Faivus

Head of Mid-Market Sales

How do you empower your team to be more creative?

We make sure we don’t ship org structures, but rather aligned products. How can our products complement one another, building upon each other to achieve our primary goals? Whether it’s scheduling, routing, predictive analytics, or operational excellence, we are acting as one, and smartly leveraging our domains and strengths.

Joe Chang

Director of Engineering, Uber Freight

How does your team reward individual success?

I believe recognizing someone’s contributions are a big part of team play. On our weekly meetings, we always start with a shout-out, and it’s amazing how this simple topic stimulates the team to recognize small victories and accredit colleagues for their accomplishments. This brings our team together and fosters a more collaborative environment.

Silvia Penna

Sr Manager, Central Operations

More Jobs at Uber

Apply Now
By clicking Apply Now you agree to share your profile information with the hiring company.
View Uber's full profileSee more Uber jobs