Job Summary:This job will design, develop, and implement machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences.
Job Description:Essential Responsibilities: - Develop and optimize machine learning models for various applications.
- Preprocess and analyze large datasets to extract meaningful insights.
- Deploy ML solutions into production environments using appropriate tools and frameworks.
- Collaborate with cross-functional teams to integrate ML models into products and services.
- Monitor and evaluate the performance of deployed models.
Minimum Qualifications:- 3+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience.
- Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
- Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
- Several years of experience in designing, implementing, and deploying machine learning models.
Additional Responsibilities & Preferred Qualifications:- PhD in Computer Science, AI/ML, NLP, or a related field - with research in one or more of: LLM agents, multi-agent systems, tool-use, reasoning, planning, dialogue systems, or reinforcement learning
- Strong engineering skills - you can take a research idea from paper to production. Python is second nature. You've built systems, not just run experiments.
- Deep familiarity with agentic frameworks and architectures - LangChain, Google ADK, or custom orchestration systems. You understand the tradeoffs.
- Experience with LLM APIs and tool-use patterns - function calling, structured outputs, retrieval-augmented generation, chain-of-thought, and prompt engineering at scale
- Understanding of evaluation methodology for AI systems - how to measure agent performance beyond academic benchmarks, including safety, hallucination rates, and task completion in adversarial conditions
- Published research is a plus - but shipping code matters more than citation count
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 | ($159,500.00 - $236,500.00 Annually)
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.
