Job Description
We are looking for exceptional Engineers, who take pride in creating simple solutions to apparently-complex problems. Our Engineering tasks typically involve at least one of the following:
- Building a pipeline that processes up to billions of items, frequently employing ML models on these datasets
- Creating services that provide Search or other Information Retrieval capabilities at low latency on datasets of hundreds of millions of items
- Crafting sound API design and driving integration between our Data layers and Customer-facing applications and components
If you love a good challenge, and are good at handling complexity - we’d love to hear from you!
eBay is an amazing company to work for. Being on the team, you can expect to benefit from:
- A competitive salary - including stock grants and a yearly bonus
- A healthy work culture that promotes business impact and at the same time highly values your personal well-being
Job Responsibilities
- Design, deliver, and maintain significant features in data pipelines, ML processing, and / or service infrastructure
- Optimize software performance to achieve the required throughput and / or latency
- Work with your manager, peers, and Product Managers to scope projects and features
- Come up with a sound technical strategy, taking into consideration the project goals, timelines, and expected impact
- Take point on some cross-team efforts, taking ownership of a business problem and ensuring the different teams are in sync and working towards a coherent technical solution
Minimum Qualifications
- Passion and commitment for technical excellence
- B.Sc. or M.Sc. in Computer Science or an equivalent professional experience
- 2+ years of software design and development experience, tackling non-trivial problems in backend services and / or data pipelines
- A solid foundation in Data Structures, Algorithms, Object-Oriented Programming, Software Design, and core Statistics knowledge
- Experience in production-grade coding in Java, and Python/Scala
- Experience in the close examination of data and computation of statistics
- Experience in using and operating Big Data processing pipelines, such as: Hadoop and Spark