Staff Machine Learning Engineer - Ranking & Recommendations (Generative AI)

Role Location: San Francisco, Sunnyvale, Seattle, or New York

A bout the Role

The Shopping Ranking Team mission is enabling eaters to effortlessly make shopping decisions and find what they need. We pursue this mission via an ML-driven algorithmic approach, applying state-of-the-art Machine Learning (ML), Optimization techniques to learn from massive datasets Uber has, and build a scalable and reliable shopping intelligence ranking and recommendation systems.

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 a deep interest in ML model, feature and infrastructure development. Candidates will have the opportunity to work across various lines, from infrastructure development to ML model development, productionalization, offering a diverse and enriching experience.

Join us in our pursuit of excellence as we are building the next generation of Generative AI - shopping ranking and recommendation systems.

What You Will Do

• Design and build Machine Learning models in Ranking and Recommendation domain.
• 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.

Basic Qualifications

• Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 4+ years of full-time engineering experience.
• 6+ 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, such as HDFS, Hive, MapReduce, Spark, , etc.
• Working knowledge of latest ML technologies, and libraries, such as PyTorch, TensorFlow, Ray, etc.
• Proven track records of being a fast learner and go-getter, with willingness to get out of the comfort zone.

Preferred Qualifications

• Experience with building ranking and recommendation systems 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 design and architecture of ML systems and workflows.
• Experience owning and delivering a technically challenging, multi-quarter project end to end.

For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits., For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.