Job Summary:

Job Description:

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:

1. Experience with the following: machine learning (ML) models, Reinforcement learning with contextual multiarmed bandits and Neural Bandit. (3 years)

2. Experience with fine tuning LLMd such as Llama, RoBERTa with PyTorch or Tensorflow using algorithms including LoRA (1 year).

3. Experience with the following tools & programming skills: PyTorch, Tensorflow, Scala, Java, and Python (4 years).

4. Experience working on low latency system and writing skills with blogs or papers (2 years).

5. Experience with training, testing and productionizing ranking models for real-time recommendation systems with strict latency constraints. (3 years)

6. 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)

7. Experience with training, testing and productionizing Two-Tower based Neural Networks for generating personalized recommendations for users. (3 years)

8. 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:

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.

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.

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.