Software Engineer II, Machine Learning

$158,000 - $175,500/Yr

Uber - San Francisco, CA

Full-time - Mid Level

Remote - San Francisco, CA

Transit and Ground Passenger Transportation

About the position

The focus of the Consumer Pricing team is to ensure the best merchant selection for consumers, innovate on pricing models for consumers to shape demand and maximize marketplace throughput. The initiatives led by this group are fundamental to the success of Uber's Delivery business by driving growth and profitability. To enable these initiatives, we invest heavily in ML and optimization tech stacks, including data ETL, feature store, dev & viz tooling, model training, serving, storage and backtest solutions. We are actively seeking individuals who excel in problem-solving and critical thinking, are proficient in coding, with proven track records of learning and growth, and have prior experience in ML model, feature, and infrastructure development.

Responsibilities

• Design and build Machine Learning models with optimization engines.
• Productionize and deploy these models for real-world application.
• Review code and designs of teammates, providing constructive feedback.
• Collaborate with Product and cross-functional teams to brainstorm new solutions and iterate on the product.

Requirements

• Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 3+ years of full-time engineering experience.
• 2+ years of ML experience and building ML models.
• Experience working with multiple multi-functional teams (product, science, product ops etc).
• Expertise in one or more object-oriented programming languages (e.g. Python, Go, Java, C++).
• Experience with big-data architecture, ETL frameworks and platforms.
• Solid understanding of latest ML technologies, and libraries.
• Proven track records of being a fast learner and go-getter, with willingness to get out of the comfort zone.

Nice-to-haves

• Experience with the design and architecture of ML systems and workflows.
• Experience with building algorithmic solutions in production, making practical tradeoffs among algorithm sophistication, compute complexity, maintainability, and extensibility in production environments.
• Experience with taking on vague business problems, translating them into ML + Optimization formulation, identifying the right features, model structure and optimization constraints, and delivering business impact.
• Experience with optimizing Spark queries for better CPU and memory efficiency.
• Experience owning and delivering a technically challenging, multi-quarter project end to end.

Benefits

• Eligible to participate in Uber's bonus program.
• May be offered an equity award & other types of compensation.
• Various benefits as detailed in the company link.