Staff Machine Learning Engineer

Posted 13 Days Ago
Be an Early Applicant
San Jose, CA, USA
In-Office
194K-334K Annually
Senior level
Fintech • Payments
The Role
Develop and deploy advanced machine learning, generative AI, ranking, and recommendation models for personalized PayPal products and customer experiences. Build scalable near-real-time feature pipelines using Flink, Kafka, and Spark. Productionize low-latency recommendation systems and Two-Tower neural networks, conduct statistical analysis for unbiased training data, and communicate technical findings to technical and non-technical stakeholders.
Summary Generated by Built In

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 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:

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.

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.

Who We Are:

Click Here to learn more about our culture and community.

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 [email protected].  

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.

Skills Required

  • Master's degree or foreign equivalent in Computer Science, Engineering, Physical Systems, or a closely related field, plus four years of experience in the offered job or a related occupation
  • Alternatively, bachelor's degree or foreign equivalent in Computer Science, Engineering, Physical Systems, or a closely related field, plus six years of experience in the offered job or a related occupation
  • Three years of experience with machine learning models, reinforcement learning with contextual multiarmed bandits, and Neural Bandits
  • One year of experience fine-tuning Llama or RoBERTa using PyTorch or TensorFlow and LoRA
  • Four years of experience with PyTorch, TensorFlow, Scala, Java, and Python
  • Two years of experience with low-latency systems and writing blogs or papers
  • Three years of experience training, testing, and productionizing ranking models for real-time recommendation systems with strict latency constraints
  • Three years of experience designing scalable near-real-time feature engineering pipelines using Apache Flink, Apache Kafka, and Apache Spark
  • Three years of experience training, testing, and productionizing Two-Tower neural networks for personalized recommendations
  • Four years of experience performing statistical analysis for unbiased training data using power analysis, Inverse Propensity Weighting, and Design Effect
  • Legal authorization to work in the United States without sponsorship

PayPal Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about PayPal and has not been reviewed or approved by PayPal.

  • Healthcare Strength Health coverage starts on the date of hire with medical, dental, vision, wellness resources, and health-navigation support. Eligibility includes spouses/domestic partners and dependents up to age 26, indicating broad and robust coverage.
  • Leave & Time Off Breadth Flexible time-off frameworks and a market-leading sabbatical after five years provide substantial time-away options. Paid leaves span bonding/parental, disability, and localized programs, offering broad coverage across situations.
  • Retirement Support A 401(k) with company match and a year-end true-up strengthens long-term savings. Financial-wellbeing tools and related programs further support retirement planning.

PayPal Insights

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The Company
HQ: San Jose, CA
34,450 Employees
Year Founded: 1998

What We Do

HELP US REIMAGINE MONEY. At PayPal, we believe that now is the time to democratize financial services so that moving and managing money is a right for all citizens, not just the affluent. We are driven by this purpose, and we uphold our cultural values of collaboration, innovation, wellness and inclusion as our guide for making decisions and conducting business every day. It is our duty and privilege to be customer champions and put those we serve at the center of everything we do. We are one team that respects and values diversity of thought for everyone, everywhere, and we actively seek to create an energizing workplace that brings out the best in all of us. If you’re ready to shape the future of money, join the team at PayPal. We're proud to work here. You will be too. PayPal is headquartered in San Jose, California and its international headquarters is located in Singapore.

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