Staff Machine Learning Engineer

Staff Machine Learning Engineer

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

Job Duties: Develop and implement advanced ML models, such as gradient boosted decision tree, graph neural networks and deep learning models, to solve critical business problems related to recommendation of PayPal products, personalizing product experiences including UI flows, and optimizing the lifecycle of the customers on the platform. Design and deploy scalable generative AI solutions as part of the ecosystem. Design and deploy scalable ML/Al solutions that enhance PayPal's ability to provide a seamless customer experience, by working closely with our engineering group and PayPal's Platforms organization. Communicate complex concepts and the results of models and analyses to both technical and non-technical audiences, influencing partners and customers with insights and expertise. Partial telecommuting permitted from within a commutable distance.

Minimum Requirements: Master's degree, or foreign equivalent, in Computer Science, Engineering, Physical Systems, or a closely related field plus four 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, Physical Systems, or a closely related field plus six years of experience in the job offered or a related occupation.

Special Skill Requirements:

• Experience with the following: machine learning (ML) models, Reinforcement learning with contextual multiarmed bandits and Neural Bandit. (3 years)
• Experience with fine tuning LLMd such as Llama, RoBERTa with PyTorch or Tensorflow using algorithms including LoRA (1 year).
• Experience with the following tools & programming skills: PyTorch, Tensorflow, Scala, Java, and Python (4 years).
• Experience working on low latency system and writing skills with blogs or papers (2 years).
• Experience with training, testing and productionizing ranking models for real-time recommendation systems with strict latency constraints. (3 years)
• Experience with designing highly scalable near real-time feature engineering pipelines using Apache Flink for stream processing, Apache Kafka as queue and Apache Spark for batch feature processing. (3 years)
• Experience with training, testing and productionizing Two-Tower based Neural Networks for generating personalized recommendations for users. (3 years)
• Experience with performing statistical analysis for robust unbiased training data using techniques such as power analysis, Inverse Propensity Weighting and Design Effect. (4 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: $193,978.00-333,500.00 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.

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 .

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 wellbeingphysical, emotional, and financialdelivering 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.

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 View email address on click.appcast.io .

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 .

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