Job Summary:

Job Description:

PayPal, Inc. seeks Staff Machine Learning Engineer in San Jose, CA

Job Duties: Design and deploy scalable Risk analytical solutions and generative AI solutions and productize Machine Learning models that enhance PayPal's ability to provide a seamless customer experience. Lead and collaborate with data scientists and system engineers to solve complex problems with machine learning and AI capabilities. Define technical standards and ensure high code quality, performance, and reliability through rigorous testing, code reviews, and adherence to software development best practices. Drive innovation by researching and incorporating state-of-the-art machine learning techniques, tools, and frameworks into the platform. Lead architecture design and technical decision-making across cross-functional groups and deliver results in matrix organizations. Develop different AI agents to automate workflow, detect live issues and provide fix suggestions. Mentor senior and junior team members, provide technical guidance and strategic direction, and foster a culture of collaboration, innovation, and continuous learning. Partial telecommuting permitted from a commutable distance.

Minimum Requirements: Master's degree, or foreign equivalent, in Computer Science, Engineering, or a closely related field plus five years of experience in the job offered or a related occupation. Employer will accept a Bachelor's degree, or foreign equivalent, in Computer Science, Engineering or a closely related field plus eight years of progressively responsible experience in the job offered or a related occupation.

Special Skill Requirements:

(1) Experience designing and deploying scalable machine learning models and pipelines in production environments using Python and Java (4 years)

(2) Experience developing and productizing Generative AI solutions, including LLMs, RAG pipelines, or AI agents (e.g., LangChain, LlamaIndex, or similar frameworks) (2 years)

(3) Experience with big data technologies and distributed computing frameworks such as Spark, Hadoop, or Flink for large-scale data processing (3 years)

(4) Experience designing and developing large-scale software applications using Object-Oriented Design in Java or Python (4 years)

(5) Experience with cloud platforms (AWS, GCP, or Azure) for deploying and managing ML/AI workloads, including containerization with Docker and Kubernetes (2 years)

(6) Experience building and maintaining data pipelines and ML feature engineering systems using tools such as Airflow, MLflow, or similar MLOps platforms (2 years)

(7) Experience in risk analytics or fraud detection domains, including model development for anomaly detection, payment risk, or transaction monitoring (2 years)

(8) Experience developing AI agents or workflow automation systems using agentic frameworks for issue detection, root cause analysis, or automated remediation (1 year)

(9) Experience with software engineering best practices including code reviews, unit/integration testing, CI/CD pipelines, and version control (e.g., Git) (4 years)

(10) Experience leading cross-functional teams of data scientists, product managers, and system engineers to deliver end-to-end ML/AI solutions in a matrix organization (3 years)

Additional Responsibilities & Preferred Qualifications:

The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is:

Primary Location | Pay Range:

San Jose, California | Salary: $227,639.00-300,500.00 per annum. 40 hours per week; M-F, 9:00 a.m. to 5:00 p.m.

Additional compensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable.

Must be legally authorized to work in the U.S. without sponsorship.

Subsidiary:
PayPal

Travel Percent:
0

PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. When making an application directly, we will never ask you to share passwords, one-time passcodes (OTP), or verification codes. Any such request is a red flag and likely part of a scam. All communication regarding your application will come from official PayPal email domains. If you suspect fraudulent activity, please report it immediately. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact-us.

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.

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 comprehensive, choice-based programs, to support all aspects of personal wellbeing-physical, emotional, and financial-delivering meaningful value where it matters most. We strive to create a flexible, balanced work culture with a holistic approach to benefits, including generous paid time off, healthcare coverage for you and your family, and resources to create financial security and support your mental health.