At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.
Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet.
Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.
About the team and the role:
eBay, Inc. seeks Software Engineer 2 in New York, NY
What you will accomplish:
Job Duties: Improve the effectiveness and efficiency of the “Similar Items” recommendation module on eBay’s product pages, which directly impacts millions of daily users. Build and maintain large-scale data processing pipelines using Scala and Apache Spark, which aggregate user interaction signals such as clicks, purchases, watchlist activity, and reviews. Utilize Hadoop Distributed File System (HDFS) to store and manage terabytes of behavioral and product data. Preprocesses this data to ensure quality, completeness, and suitability for downstream machine learning tasks. Analyze structured and unstructured data using SQL and Python (with libraries such as Pandas and NumPy) to extract meaningful user preferences and behavioral patterns, including implicit feedback and negative signals. Develop and integrate new features into the recommendation model based on behavioral insights, leveraging domain knowledge and statistical methods to improve model expressiveness. Implement deep learning-based recommended models using PyTorch, incorporating user and item embeddings, attention mechanisms, and custom loss functions to optimize for relevance and diversity. Conduct both offline evaluations and online A/B testing to assess model performance. Use results to iterate and refine models based on statistical significance and business KPIs. Collaborate closely with product managers, data scientists, and backend engineers to align recommendation strategies with user experience goals and business outcomes. Partial telecommuting permitted from within a commutable distance.
What you will bring:
Minimum Requirements: Master’s degree, or foreign equivalent, in Computer Science, Engineering (any field), or a closely related field.
Special Skill Requirements:
1. SQL Queries - Experience writing complex SQL queries to extract, join, and aggregate user behavior and item metadata from large-scale relational databases to train and evaluate recommendation models.
2. Python Programming - Experience developing and maintaining data pipelines, experimentation frameworks, and model training scripts using Python and related libraries such as Pandas, NumPy, and Scikit-learn.
3. Machine Learning - Experience designing and training machine learning models for ranking, personalization, and user-item relevance prediction in large-scale recommendation systems.
4. API Development - Experience building and maintaining RESTful APIs to serve model predictions and integrate recommendation results into company’s buyer experience and experimentation platforms.
5. Algorithm Development - Experience implementing and optimizing algorithms for candidate retrieval and ranking to improve recommendation accuracy and diversity.
6. Data Structures - Experience utilizing efficient data structures (e.g., hash maps, heaps, trees, sparse matrices) to handle large-scale user-item interaction data and accelerate model computation.
7. Recommendation Systems - Experience developing end-to-end recommendation pipelines including candidate generation, ranking, and post-processing to enhance personalization and engagement across company’s marketplace.
8. LLMs (Large Language Models) - Experience leveraging large language models for semantic understanding of item titles and descriptions, query expansion, and improving cold-start recommendations.
9. NLP (Natural Language Processing) - Experience applying NLP techniques such as embeddings, text classification, and semantic similarity modeling to extract insights from listing text and user queries.
10. Predictive Modeling - Experience building and validating predictive models to estimate user engagement metrics and forecast demand patterns for personalized recommendation strategies.
11. Hadoop & Spark Big Data Processing ETL - Experience using Hadoop and Spark to process terabytes of behavioral and transactional data, performing ETL to prepare features and datasets for large-scale machine learning training and evaluation.
Salary: $131,997.00-229,600.00 per annum. 40 hours per week; M-F, 9:00 a.m. to 5:00 p.m.
Must be legally authorized to work in the U.S. without sponsorship.
Additional Details
Base pay offered may vary depending on multiple individualized factors, including location, skills, and experience. The total compensation package for this position may also include other elements, including a target bonus and restricted stock units (as applicable) in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as PTO and parental leave). Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
If hired, employees will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.
Remote roles are not eligible for U.S. visa sponsorship.
eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at [email protected]. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility for people with disabilities.
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Skills Required
- Master's degree in Computer Science, Engineering, or closely related field
- Experience writing complex SQL queries for large-scale data extraction and aggregation
- Python programming experience (Pandas, NumPy, Scikit-learn) for data pipelines and model training
- Machine learning experience designing and training ranking/personalization models
- Experience building and maintaining RESTful APIs to serve model predictions
- Algorithm development experience for candidate retrieval and ranking
- Proficiency with data structures to handle large-scale user-item interaction data
- Experience developing end-to-end recommendation pipelines (candidate generation, ranking, post-processing)
- Experience leveraging large language models for semantic understanding and cold-start recommendations
- NLP experience (embeddings, text classification, semantic similarity) applied to listings and queries
- Predictive modeling experience for engagement metrics and demand forecasting
- Hadoop and Spark experience for big-data ETL and processing of terabytes of data
- Must be legally authorized to work in the U.S. without sponsorship
eBay Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about eBay and has not been reviewed or approved by eBay.
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Healthcare Strength — Medical, dental, and vision coverage begin on the date of hire, complemented by mental health resources, an EAP, disability coverage, FSAs, and wellness initiatives.
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Leave & Time Off Breadth — A robust mix of PTO, paid holidays, flexible work styles, parental leave, and a four‑week paid sabbatical after five years supports work‑life balance.
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Equity Value & Accessibility — Total compensation commonly includes stock components, with access to an employee stock purchase plan at a discount and stock awards enhancing overall packages.
eBay Insights
What We Do
eBay Inc. is a global commerce leader that connects millions of buyers and sellers around the world. We exist to enable economic opportunity for individuals, entrepreneurs, businesses and organizations of all sizes. Our portfolio of brands includes eBay Marketplace and eBay Classifieds Group, operating in 190 markets around the world. We offer sellers the ability to grow a business with little barrier to entry regardless of size, background or geographic location. We never compete with our sellers. We win when our sellers succeed. Buyers who shop on our Marketplace and Classifieds platforms enjoy a highly personalized experience with an unparalleled selection at great value.







