Sr Machine Learning Engineer at Uber in Sunnyvale, CA

As an engineer you will have a lot of opportunities to work with product managers, data scientists and of course engineers from other teams. You will participate the whole development cycle of a software product from product scoping, architecture design, software implementation, to productionizing, and learn how to iterate a product for greater success. We own a few key products that directly impact Uber's bottom line. We are a data driven team, and you will be able to see the impact of your work reflected in Uber's earning report, such as gross booking, trips and number of active users. The least thing you need to worry about is scope and visibility. We have many different roles in the team, and need a broad range of skills such as machine learning, data, optimization, and platform/infrastructure engineering. This is an outstanding opportunity to grow your career and do highly impactful fun things at the same time.

What the Candidate Will Do

• Work on Machine learning related efforts as part of Fares
• Solve open ended business problems to drive engagement & derive long term growth by building and maintaining platform for all Uber's Fares Ridesharing system
• Work closely with Product, Data Science and other engineering teams to add new features and scale the platform
• Lead and mentor other specialists on the team

Basic Qualifications

• 2+ years of Machine Learning, Software Engineering, Data mining experience (training, building & productionizing models) or a recent PhD graduate in relevant fields (EE, CS, Stats, Math, etc)
• Experience coding in Java, Golang or any similar languages.
• Deep knowledge of data structure and algorithms and an ability to use them practically when implementing solutions
• Knowledge of data-driven architecture and systems design

Preferred Qualifications

• 5+ years of software engineering experience, or 3+ years of software engineering experience with PhD in relevant fields (EE, CS, Stats, Math, etc)
• Experience with converting business problems into ML problems
• Experience with causal learning and/or deep learning
• Experience working with large dataset storage systems like NoSQL, HDFS (+Hive) and data distribution systems like Kafka
• Engineering experience in hands-on software development with thoughtfulness of scale, latency and distributed architecture
• A willingness and curiosity to learn both the systems and domain in which you will be solving problem statements
• A great teammate and owner- willing to take on ownership of the systems, and think about operations, maintenance and reliability of his/her systems