PayPal Staff Machine Learning Engineer United States, California, San Jose 897849204
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Essential Responsibilities:
- Lead the development and optimization of advanced 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.
Expected Qualifications:
- 5+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
- Extensive experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
- Expertise in cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
Your Day-to-Day
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, orsimilar toenable complex multi-agent interactions.
Perform advanced context and prompt engineering,optimizingmulti-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.
Bring
Master’s degree (or higher) in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative discipline.
5+ years of relevant industry experience (or 4+ years with a PhD).
Deep understanding of Transformer architectures and hands-on experience with fine-tuning LLMs for production use cases.
proficiencyin Python and ML frameworks such asPyTorch, TensorFlow, or JAX.
Demonstrated experience with Agentic frameworks such as A2A, MCP,LangGraph,LangChainorsimiliar, 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 withMLOps/LLMOpspractices — model deployment, monitoring, and continuous retraining at scale.
Excellent communication skills with the ability to collaborate across engineering, research, and product teams.
Travel Percent:
The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .
The US national annual pay range for this role is $169,500 to $291,500
Our Benefits:
Any general requests for consideration of your skills, please
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