Sr Machine Learning Scientist, Agentic AI
Listed on 2026-01-12
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer, Data Scientist
About Pay Pal
Pay Pal has been revolutionizing commerce globally for more than 25 years, creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure. With operations in approximately 200 markets, Pay Pal empowers consumers and merchants to thrive in the global economy.
Job SummaryPay Pal is seeking a Sr. Staff Machine Learning Scientist to drive the next evolution of Venmo’s Agentic Experiences—an innovative paradigm redefining how users interact with Venmo through intelligent, context‑aware, and autonomous AI systems.
Job Description- 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 deployed models, making necessary adjustments.
- Mentor and guide junior engineers and data scientists.
- Ensure adherence to best practices and industry standards in ML development.
- 8+ years of relevant experience and a Bachelor’s degree OR equivalent combination of education and experience.
- Deep expertise with ML frameworks like Tensor Flow, PyTorch, or scikit-learn.
- Extensive experience with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
- Proven track record of leading the design, implementation, and deployment of machine learning models.
- 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), Lang Graph, or similar.
- 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.
- 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, Tensor Flow, or JAX.
- Demonstrated experience with Agentic frameworks such as A2A, MCP, Lang Graph, or Lang Chain, 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.
You’ll be part of the team pioneering Venmo’s intelligent, agentic future—building AI systems that think, adapt, and act on behalf of users to simplify financial interactions. This is a unique opportunity to work at the intersection of machine learning, LLM research, and human‑centered product design, driving the evolution of one of the most trusted financial brands in the…
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