

What Will You Do
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
Designing and running A/B tests in Production experiences in order to vet and measure the impact of any new or improved functionality
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
Being part of a force for good in this world - eBay truly cares about its employees, its customers, and the world’s population, and takes every opportunity to make this clearly apparent
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
Take active part in knowledge sharing across the organization - both teaching and learning from others
Minimum Qualifications
Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field with 6+ years of relevant industry experience, including 3+ years in people management.
Proven experience leading machine learning teams in an applied industrial setting.
Deep understanding of modern ML approaches including classification, regression, NLP, clustering, deep learning, and/or reinforcement learning.
Strong programming background in Python, Java, or similar, with exposure to production-grade ML systems.
Proficiency with big data processing frameworks such as Hadoop, Spark, and SQL.
Excellent communication, storytelling, and stakeholder management skills.
Demonstrated ability to translate business needs into scientific problems and to prioritize for impact.
Additional Qualifications
Master’s or Ph.D. in a relevant field (Computer Science, ML, Stats, etc.)
Track record of impactful publications and/or patents in machine learning or related areas.
Contributions to open-source ML tools or frameworks.
Experience with modern large language models, graph-based ML, or knowledge graph construction.
Strong presence in scientific communities through talks, panels, or organizing roles.
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