Software Engineer II, Machine Learning (multiple teams hiring)

$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 Software Engineer II, Machine Learning role focuses on designing and building machine learning models and optimization engines to enhance Uber's delivery business. The position involves collaborating with cross-functional teams to innovate pricing models and ensure efficient merchant selection for consumers. Candidates are expected to have a strong background in machine learning, coding, and problem-solving, contributing to the development and deployment of ML solutions in a production environment.

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

• Participation in Uber's bonus program.
• Equity award opportunities.
• Various health and wellness benefits.