Senior Staff Machine Learning Engineer

PayPal; San Jose (CA); Hybrid; USD 228,000 - 301,000; Full time

Benefits offered by this job

Generous paid time off

Healthcare coverage for you and your/fi

Resources for financial security and健康

Job summary

PayPal in San Jose, CA seeks a Senior Staff Machine Learning Engineer to architect ML-driven software features, collaborate across engineering and data science teams, and optimize models for production. The role emphasizes scalable ML pipelines, data analytics, and robust testing within a fast-paced fintech environment.

The position includes a balanced hybrid work model with partial telecommuting, competitive compensation, and benefits.

Qualifications

• Experience developing ML models end-to-end.
• /nExperience with managing external facing ML models.
• nExperience with ML tooling.
• nExperience assessing predictive value of features.
• nExperience with Python and SQL (8 years).
• nExperience with Credit and Fraud Risk models.
• nExperience in distributed computing technologies like Spark.
• nBanking/fintech experience and Model Risk Management requirements.
• nExperience with AWS/Azure/GCP (8 years).
• nExperience with data processing and model deployment tools (8 years).
• nExperience leading the design, implementation, and deployment of ML models (6 years).
• nExperience CI/CD pipelines (6 years).
• nExperience PyTorch, TensorFlow, XGBoost, Scikit-learn (6 years).
• nExperience AWS SageMaker (6 years).
• nExperience Natural Language Processing (8 years).
• nExperience Statistical Models (8 years).
• nExperience Agile Methodology (5 years).
• nExperience Artificial Neural Networks (8 years).

Responsibilities

• Define and drive the strategic vision for implementing ML into the software ecosystem.
• Analyze software product architecture to create ML models and data pipelines.
• Collaborate with Engineering and Data Science teams to develop features meeting requirements.
• Lead optimization of ML models for production deployment and performance.
• Monitor deployed models and adjust as needed.
• Organize and analyze large datasets using cloud platforms and data processing tools.
• Create automated tests and deliver high-quality code with CI/CD.
• Support the hybrid work model with partial telecommuting within commutable distance.

Skills

ML end-to-end

External facing ML models

ML tooling

Predictive feature assessment

Python & SQL

Credit & Fraud Risk models

Distributed computing (Spark)

Model Risk Management in fintech

Cloud platforms (AWS/Azure/GCP)

Data processing & deployment tools

ML model design & deployment

CI/CD pipelines

PyTorch

TensorFlow

XGBoost

Scikit-learn

AWS SageMaker

Natural Language Processing

Statistical Modeling

Agile Methodology

Artificial Neural Networks

Education

Bachelor's degree in CS/DS/IS

Tools

PyTorch

TensorFlow

XGBoost

Scikit-learn

AWS SageMaker

Spark

Job description

The Company

PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy.

We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers.

We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade.

Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities.

Job Summary

Job Description:

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

Job Duties

Define and drive the strategic vision for implementing machine learning (ML) functions into the software ecosystem. Analyze software product architecture to create ML models using algorithmic programming techniques, database management practices, data visualization methods, and related query languages. Collaborate with Engineering and Data Science teams throughout the design and development phases to create new and enhanced software products and features consistent with business and technical requirements, with a focus on functionality, performance, scalability, reliability, realistic implementation schedules, and adherence to development goals and principles. Lead the optimization of ML models to integrate them into products and services. Monitor and evaluate the performance of deployed models, making necessary adjustments. Organize and analyze large datasets using experience with cloud platforms and tools for data processing and model deployment. Create and implement data analytics pipelines into existing software. Deploy and maintain ML solutions in production environments. Define and design testing sequences for newly developed software to implement into the ML pipeline. Create automated tests and deliver high-quality software code to production within a short development cycle in the continuous integration and delivery environment.
Partial telecommuting permitted from within a commutable distance.

Minimum Requirements

Minimum Requirements: Bachelor’s degree, or foreign equivalent, in Computer Science, Data Science, Information Systems, or a closely related field plus 8 years of progressively responsible experience in the job offered or a related occupation.

Special Skill Requirements

• (1) Experience developing ML models end-to-end
• (2) Experience with managing external facing ML models
• (3) Experience in ML tooling
• (4) Experience assessing predictive value of features
• (5) Experience with Python and SQL programming languages (8 years)
• (6) Experience with Credit and Fraud Risk models
• (7) Experience in distributed computing technologies like Spark
• (8) Banking and fintech experience and experience with Model Risk Management requirements
• (9) AWS, Azure, or GCP (8 years)
• (10) Tools for data processing and model deployment (8 years)
• (11) Experience leading the design, implementation, and deployment of machine learning models (6 years)
• (12) Continuous Integration and Continuous Delivery (CI/CD) Pipelines (6 years)
• (13) PyTorch, TensorFlow, XGBoost, and Scikit-learn Machine Learning Libraries (6 years)
• (14) AWS SageMaker (6 years)
• (15) Natural Language Processing (8 years)
• (16) Statistical Models (8 years)
• (17) Agile Methodology (5 years)
• (18) Artificial Neural Networks (8 years)

Additional Responsibilities & Preferred Qualifications

EOE, including disability/vets.

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.

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

• generous paid time off
• healthcare coverage for you and your family
• resources to create financial security and support your mental health

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 [e-mail].

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.

We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates.