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Über
As a Machine Learning Engineer, you’ll contribute to key components of the product search stack - including indexing pipelines, and query-time services that deliver fast and relevant search results. You’ll collaborate closely with backend engineers and catalog data teams to enable intelligent, contextual, and scalable search capabilities.
We’re looking for motivated and collaborative engineers who thrive on solving complex problems in large‑scale search systems. You will work on challenges such as query and document understanding, product entity modeling and enrichment, taxonomy structuring, retrieval and ranking algorithms, and search quality evaluation. You will build models that enhance search relevance and ranking, delivering highly relevant results to users across the PayPal ecosystem. The ideal candidate brings strong experience in machine learning systems, takes ownership of the project from research and prototyping to production deployment, and is eager to shape modern, AI‑powered search experiences.
Responsibilities:
Lead the development and optimization of advanced machine learning models.
Oversee the preprocessing and analysis of large datasets.
Deploy and maintain ML solutions in production environments.
Collaborate with cross‑functional teams to integrate ML models into products and services.
Monitor and evaluate the performance of deployed models, making necessary adjustments.
Expected Qualifications:
5+ years relevant experience and a Bachelor’s degree OR any equivalent combination of education and experience.
Extensive experience with ML frameworks like TensorFlow, PyTorch, or scikit‑learn.
Expertise in cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
Additional Responsibilities & Preferred Qualifications:
8+ years of industry experience with deep learning architectures, building, fine‑tuning and deploying ML models in production.
Strong proficiency in Python, Scala, or other programming languages.
Experience working with large datasets, data processing pipelines (e.g., Dataflow, Spark, Flink), and scalable architectures.
Strong communication and collaboration skills, with the ability to work effectively across teams and contribute to a high‑performing engineering culture.
Experience working on search or recommendation systems at scale.
Familiarity with A/B testing and experimentation methodologies for search relevance improvement.
The pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay, including base pay and commission‑based compensation, for this role by location is: For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in‑person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.
Primary Location | Pay Range: For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in‑person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.
Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com.
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Sprachkenntnisse
- English
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