Uber Software Engineer II - Machine Learning 

United States, West Virginia 

200760249

About the Role

- - - - What the Candidate Will Do ----

• Innovate and productionize start-of-the-art recommendation models, and customize for Uber’s use cases.
• Design and build the end-to-end large-scale ML systems to power the HomeFeed Recommendation.
• Improve the Feed Model ML Quality, Model Serving foundation and the Data foundation.
• Collaborate with cross-functional and cross-team stakeholders.

- - - - Basic Qualifications ----

• PhD in relevant fields (CS, EE, Math, Stats, etc.) with recommendation system research experiences or 2 years minimum of industry experience with a strong focus on machine learning and recommendation systems.
• Expertise in deep learning, recommendation systems, or optimization algorithms.
• Experience with ML frameworks such as PyTorch and TensorFlow.
• Experience building and productionizing innovative end-to-end Machine Learning systems.
• Proficiency in one or more coding languages such as Python, Java, Go, or C++.
• Experience with any of the following: Spark, Hive, Kafka, Cassandra.
• Strong communication skills and can work effectively with cross-functional partners.

- - - - Preferred Qualifications ----

• Publications at industry recognized ML conferences.
• Experience in simplifying/converting business problems into ML problems.
• Experience developing complex software systems scaling to millions of users with production quality deployment, monitoring and reliability.

For New York, NY-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.

For San Francisco, CA-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.

For Seattle, WA-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.