Machine Learning Scientist, Agentic AI

PayPal•San Jose, CA

2d•Hybrid

About The Position

PayPal is seeking a Machine Learning Scientist to lead the next evolution of Agentic Experiences for Commerce and Shopping — a paradigm shift redefining how users discover and purchase products through intelligent, autonomous, and context-aware AI systems. In this role, you’ll be a key contributor to both the product vision and AI architecture, driving innovations across the entire ecosystem — from system design and LLM fine-tuning to context engineering, evaluation, and deployment. Your work will enable personalized, proactive, and conversational shopping experiences powered by state-of-the-art large language models and agentic frameworks. This position is ideal for those deeply passionate about Agentic AI, LLM customization, and building interactive, scalable shopping experiences that transform how people engage with commerce.

Requirements

1+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
Familiarity with ML frameworks like TensorFlow or scikit-learn.
Strong analytical and problem-solving skills.

Nice To Haves

Master’s degree (or higher) in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative discipline.
3+ years of relevant industry experience (or 2+ years with a PhD).
Deep understanding of Transformer architectures and hands-on experience with fine-tuning LLMs for production use cases.
Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX.
Demonstrated experience with Agentic frameworks such as A2A, MCP, LangGraph, LangChain or similiar, and an understanding of Agent-Oriented Design patterns.
Experience building context-aware conversational systems, integrating multi-source data for reasoning and response generation.
Knowledge of LLM and agentic evaluation methodologies, including prompt testing, offline metrics, and human feedback loops.
Familiarity with MLOps/LLMOps practices — model deployment, monitoring, and continuous retraining at scale.
Excellent communication skills with the ability to collaborate across engineering, research, and product teams.

Responsibilities

Assist in the development and optimization of machine learning models.
Preprocess and analyze datasets to ensure data quality.
Collaborate with senior engineers and data scientists on model deployment.
Conduct experiments and run machine learning tests.
Stay updated with the latest advancements in machine learning.
Design, develop, and evolve Commerce Agentic System, advancing its reasoning, memory, and action layers to create dynamic, context-aware user experiences.
Fine-tune large language models (LLMs) for commerce and shopping applications, ensuring robust alignment, safety, and personalization.
Implement and extend agentic frameworks such as A2A (Agent-to-Agent), MCP (Model Context Protocol), LangGraph, or similar to enable complex multi-agent interactions.
Perform advanced context and prompt engineering, optimizing multi-turn, multi-source model orchestration for superior performance and responsiveness.
Collaborate cross-functionally with product, design, and platform engineering teams to define the next generation of agentic capabilities and AI interface strategies.
Experiment with reinforcement learning, retrieval-augmented generation (RAG), and online adaptation to refine agent behavior and enhance response quality.
Build scalable, production-ready pipelines for model training, evaluation, and continuous improvement.
Communicate insights and technical trade-offs clearly to influence both engineering decisions and PayPal’s broader AI strategy.

Benefits

medical, dental, vision, life and disability insurance, parental and family leave, 401(k) savings plan, paid time off, and other benefits
flexible work environment
employee shares options
health and life insurance

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