Machine Learning Engineer PhD Intern

The Machine Learning Engineer PhD Intern at PayPal will leverage advanced machine learning and cutting-edge research to design innovative solutions for compliance, risk mitigation, and a secure financial experience. This role involves hands-on experience with large language models (LLMs) and ML projects in commerce, personalization, recommendation, and user behavior understanding. Interns will assist in fine-tuning, evaluating, and deploying LLMs, collaborate with experts, analyze data, build prototypes, and explore new methodologies to enhance personalization and recommendation systems.

Must Have

• Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, or a related field.
• Strong understanding of machine learning concepts, algorithms, and techniques.
• Familiarity with large language models (LLMs) and related techniques.
• Proficiency in Python and ML libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Hugging Face.
• Experience with data analysis, cleaning, and wrangling.
• Strong theoretical foundation in ML algorithms, optimization, and statistical learning theory.
• Must be enrolled in a PhD program and returning to studies after the internship.
• Must reside in the U.S. during the program.
• Must be authorized to work in the U.S. for the duration of the internship.

Good to Have

• Experience conducting independent research with publications in relevant ML/AI conferences or journals.

Perks & Benefits

• Flexible work environment
• Employee shares options
• Health insurance
• Life insurance
• Medical benefits
• Dental benefits
• Vision benefits
• Other benefits

Key Responsibilities:

• Gain hands-on experience working on real-world large language model (LLM) and machine learning projects within the domains of commerce, personalization, recommendation, and user behavior understanding.
• Assist in the fine-tuning, evaluation, and deployment of LLMs for tasks such as personalized recommendations, semantic search, and behavioral modeling.
• Collaborate with experienced engineers, data scientists, and product experts to translate business requirements into actionable LLM and ML-driven solutions.
• Analyze data, build prototypes, and explore new methodologies to improve the effectiveness of personalization and recommendation systems.
• Contribute to the development and documentation of LLM training pipelines and model evaluation frameworks, ensuring reproducibility and maintainability.
• Present findings and recommendations to stakeholders across the organization, highlighting the business impact of personalization and LLM applications.
• Network with talented professionals and gain valuable insights into the world of financial technology, personalization, and applied machine learning.

Basic Requirements:

• Strong understanding of machine learning concepts, algorithms, and techniques (e.g., supervised learning, unsupervised learning, deep learning).
• Familiarity with large language models (e.g., GPT, LLaMA, Mistral) and techniques for fine-tuning, prompt engineering, or embeddings-based retrieval.
• Proven ability to work with Python, libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, and Hugging Face Transformers.
• Experience with data analysis, cleaning, and wrangling.
• Excellent communication, collaboration, and problem-solving skills.
• A passion for learning and exploring new technologies.
• Highly motivated and proactive with a strong work ethic.

Basic Requirements

• Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, or a related field.
• Strong theoretical foundation in ML algorithms, optimization, and statistical learning theory.
• Demonstrated ability to implement and evaluate ML models using Python and libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, and PyTorch.
• Experience conducting independent research, with publications in relevant ML/AI conferences or journals (preferred).
• Excellent communication and collaboration skills, with the ability to present research to both technical and non-technical audiences.
• Highly motivated, curious, and proactive in exploring new research directions.

Program Information and Requirements

• This is a Summer 2026 PhD Internship (Spring and Fall sessions are not available).
• Must be enrolled in a PhD program at an accredited university, returning to studies after the internship.
• Must reside in the U.S. during the program.
• Must be authorized to work in the U.S. for the duration of the internship.

Additional Responsibilities & Preferred Qualifications:

We are committed to fair and equitable compensation practices.

Actual compensation is based on various factors including but not limited to work location, and relevant skills and experience.

The total compensation for this position may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit https://www.paypalbenefits.com

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The U.S. national hourly pay range for this role is $66/hour.

Travel Percent:

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We do not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. Any such request is a red flag and likely part of a scam. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact-us

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For the majority of employees, our balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.

Our Benefits:

At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you.

We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit https://www.paypalbenefits.com

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Who We Are:

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Commitment to Diversity and Inclusion

We provide 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, we 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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Belonging at PayPal:

Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal.

Any general requests for consideration of your skills, please Join our Talent Community

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We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply.