Senior Machine Learning Engineer - Uber AI at Uber (San Francisco, CA)

| San Francisco, CA
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Senior Machine Learning Engineer - Uber AI
About the role:
Partners with stakeholders to design, develop, optimize, and productionize machine learning (ML) or ML-based solutions and systems that are used within a team to solve complex problems with multiple dependencies. This role also leads team efforts to leverage and improve ML infrastructure for model development, training, deployment needs and scaling ML systems.
About the Team:
Uber AI is an integrated technology and research organization. The mission of Uber AI is to make AI and machine learning maximally impactful at Uber by pushing the frontiers of research, developing high quality scalable platforms, and collaborating on innovative applications. To further this mission, the group brings together AI-focused engineering, product, and research teams under a single umbrella to ensure cutting-edge AI innovation is rapidly transferred into company-wide platforms, accelerating Uber's positive impact on the world.
Our team at Uber AI works on optimization problems in the Uber marketplace, including pricing, incentives and forecasting, using deep learning and causal methodology.
What You'll Do
  • Collaborate with partner teams across Uber on the design, development, optimization, and productionization of machine learning solutions and systems for core business problems.
  • Develop innovative ML/AI solutions for challenging business problems that are fundamental for Uber
  • Collaborate with data science and engineering teams to integrate and validate ML solutions end-to-end
  • Deliver enduring value in terms of software and modeling artifacts
Minimum qualifications:
  • PhD or equivalent in Computer Science, Engineering, Mathematics or related field OR 3-years full-time Software Engineering work experience, WHICH INCLUDES 2-years total technical software engineering experience in one or more of the following areas:
  • Programming language (e.g. C, C++, Java, Python, or Go)
  • Training using data structures and algorithms
  • Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning)
  • Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib
  • Note the 2-years total of specialized software engineering experience may have been gained through education and full-time work experience, additional training, coursework, research, or similar (OR some combination of these). The years of specialized experience are not necessarily in addition to the years of Education & full-time work experience indicated.
Technical skills:
Preferred:
  • 5+ years of industry/academic experience
  • Demonstrable expertise in machine learning, especially deep learning.
  • Experience in causal inference

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 600 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 a 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.
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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

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