Sr Software Engineer

Employer: Uber Technologies, Inc.

Job Title: Sr Software Engineer

Job Location: New York, New York

Job Type: Full Time

Rate of Pay: $202,000 to $246,000 per year

You will be eligible to participate in Uber's bonus program, and may be offered other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits .

Duties: Design, develop, and test software applications using company technology stack. Apply technical knowledge to evaluate complex data, developments, and projects in order to provide recommendations to resolve technical issues. Support the company's business operations and improve engineering productivity. Build software components that can be integrated into a fully functional software system. Solve production issues in product and system reliability. Design and build Machine Learning models in Ranking and Recommendation domain. Productionize and deploy these models for large-scale real-world application. Analyze and extract relevant information from large amounts of various data and design algorithms to explore users' latent interests efficiently. Design, develop, evaluate and iterate on predictive models for candidate generation and ranking, including, but not limited to building real-time data pipelines, feature engineering, model optimization and innovation. Design and build supporting/debugging tools as needed. May telecommute.

Employer will accept a Master's degree in Computer Science, Engineering (Any), Information Technology, Mathematics, Physics, or related field and 4 years of experience in the job offered or in a related occupation.

Position Requires

• C++, Python, Java, GIT, or SVN;
• SQL or MySQL;
• Data structures and algorithms development and functionality;
• Designing technology stacks;
• Debugging and monitoring for production services;
• Distributed systems;
• Software Development Lifecycle;
• Deep learning, embedding model and recommendation systems;
• Deep learning Tools such as pytorch or tensorflow;
• Large-scale data mining and data processing using Spark;
• Optimizing inference for large Deep Learning models;
• Statistical Modeling.