About 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 a Senior Machine Learning Engineer who excels in problem-solving and critical thinking, is proficient in coding, with proven track records of learning and growth, and has 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 shopping ranking and recommendation systems.
What The Candidate Will Need / Bonus Points
---- What the Candidate 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.
- 4+ 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 New York, NY-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 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. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits., For New York, NY-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 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. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.