About the Role
- - - - 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 2+ years of full-time engineering experience.
- 1+ 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$158,000 per year - USD$175,500 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.