Sr Staff Machine Learning Scientist, Agentic AI

PayPal•San Jose, CA

7d•$218,000 - $323,950•Hybrid

About The Position

PayPal is seeking a Senior Staff Machine Learning Scientist to drive the next evolution of Venmo’s Agentic Experiences — a new paradigm redefining how users interact with Venmo through intelligent, context-aware, and autonomous AI systems. In this role, you will be a key contributor to the design and development of Venmo’s Agentic interface, helping shape both the product vision and the underlying AI architecture. You will work on everything from agentic system design and orchestration to LLM fine-tuning, context engineering, evaluation, and deployment. Your work will enable Venmo to deliver personalized, proactive, and conversational experiences powered by advanced large language models and cutting-edge agent frameworks. This role is ideal for candidates who are deeply passionate about Agentic programming, LLM customization, and building intelligent, interactive financial experiences at scale.

Requirements

8+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
Deep expertise with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
Extensive experience with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.

Nice To Haves

Master’s degree (or higher) in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative discipline.
7+ years of relevant industry experience (or 6+ 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, or LangChain, and an understanding of Agent-Oriented Design patterns.
Experience building context-aware conversational systems, integrating multi-source data for reasoning and response generation.
Familiarity with evaluation methods for LLMs and agentic systems, including prompt testing, offline metrics, and human feedback loops.
Experience with MLOps and LLMOps workflows, including model deployment, monitoring, and iterative retraining at scale.
Excellent communication skills with the ability to collaborate across engineering, research, and product teams.

Responsibilities

Define and drive the strategic vision for machine learning initiatives within the team.
Lead the development and optimization of machine learning models.
Oversee the preprocessing and analysis of large datasets.
Deploy and maintain ML solutions in production environments.
Collaborate with cross-functional teams to integrate ML models into products and services.
Monitor and evaluate the performance of deployed models, making necessary adjustments.
Mentor and guide junior engineers and data scientists.
Ensure adherence to best practices and industry standards in ML development.
Design, develop, and evolve Venmo’s Agentic system, including its reasoning, memory, and action layers to deliver dynamic, context-aware user experiences.
Fine-tune large language models (LLMs) for Venmo-specific use cases, 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 model responses and orchestrating multi-turn, multi-source interactions.
Collaborate closely with product, design, and platform engineering teams to shape Venmo’s next-generation Agentic product capabilities and AI interface roadmap.
Experiment with reinforcement learning, retrieval-augmented generation (RAG), and online adaptation to improve agent behavior and response quality.
Develop scalable, production-ready LLM and agentic pipelines, including data preparation, model training, evaluation, and continuous improvement.
Communicate insights and technical trade-offs clearly across technical and business teams to guide decision-making and influence Venmo’s broader AI strategy.