The company is looking to solve the problem of optimizing customers' navigation experience and driving long-term growth through the development of scalable offline and online ML platforms to support ranking and recommendation.
Requirements
- Experience with Big Data tools and ETL frameworks (Hadoop, Hive, Presto, Spark, Scala, Apache Airflow, etc.)
- Experience with ML frameworks such as Tensorflow and Pytorch
- Experience with deploying highly robust and scalable data pipelines processing petabytes of data
- Experience in managing mission critical services with high throughput and low latency
- Experience with integrating applications and platforms with cloud technologies (i.e, AWS and GCP)
- Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance
Responsibilities
- Proactively drive the execution of end-to-end data platform, data quality roadmap for Search & Discovery ML efforts
- Take ownership, consolidate and optimize the Search & Discovery core data logging, processing, and ML model training pipelines
- Develop and scale data infrastructure that powers batch and real-time data processing, monitoring, and debugging for ML experiments
- Drive design and implementation of scalable ML based ranking system and online ML inference services
- Research, analyze and select technical approaches for solving difficult and challenging development and integration problems
- Coach and mentor other engineers in process and methodologies
Other
- BS or MS degree in Computer Science or related field, or equivalent practical experience
- 10+ years of experience
- Strong verbal and written communication skills
- Ability to conduct meetings and make professional presentations, and explain complex concepts and technical material to non-technical users
- 18-21 days of the Paid Time Off (PTO) a year based on the tenure
- 12 Public Holidays
- Paid Parental leave
