Staff ML Engineer – Shopping Ranking and Recommendations
| Company | Uber |
|---|---|
| Location | San Francisco, CA, USA, Sunnyvale, CA, USA |
| Salary | $223000 – $248000 |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Senior, Expert or higher |
Requirements
- Bachelor’s degree in Computer Science, Engineering, Mathematics or related field
- 4+ years of experience in software engineering with an emphasis on data-driven methodologies, deep learning, and online experimentation
- Strong problem-solving skills, with expertise in ML methodologies
- 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.
Responsibilities
- Provide technical leadership to a passionate, experienced, and diverse engineering team.
- Manage project priorities, deadlines and deliverables and design, develop, test, deploy and maintain ML solutions.
- Raise the bar of ML engineering by improving best practices, producing exemplary code, documentation, automated tests and thorough & precise monitoring, and applying model debugging & interpretation techniques.
- Partner with product owners, data scientists and business teams to translate key insights and business opportunities into technical solutions.
Preferred Qualifications
- 6+ years of experience in ML experience and building ML models
- Experience in designing and crafting scalable, reliable, maintainable and reusable ML solutions using deep-learning techniques and statistical methods.
- 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 owning and delivering a technically challenging, multi-quarter project end to end.
- 2+ years of experience working in a cross-functional and/or cross-business projects, partnering with Product, Scientists, and cross-org leads to shape the team’s strategies
- Passionate about helping junior members grow by inspiring and mentoring engineers