Job Summary:As a Staff Engineer, you will lead the design, development, and implementation of advanced machine learning (ML), large language model (LLM), and agentic AI systems that solve complex business and customer problems. You will translate emerging AI capabilities into scalable, reliable solutions that improve products, strengthen internal operations, and create measurable business value. This role combines hands-on engineering, architectural leadership, and close collaboration with data scientists, software engineers, product managers, and business stakeholders.
Job Description: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.
Minimum 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.
Additional Responsibilities & Preferred Qualifications:Preferred Qualifications:- Master's or PhD in Computer Science, Machine Learning, or related fields.
- Proven experience designing and developing deep neural network (DNN) solutions.
- Experience building large-scale ads, recommendation, search, and ranking systems, and user modeling (e.g., personalization, embeddings, retrieval, learning-to-rank, and user behavior and intent modeling).
- Hands-on experience building and shipping LLM applications in production, including fine-tuning (e.g., LoRA/PEFT), retrieval-augmented generation (RAG), and prompt engineering.
- Experience designing agentic systems with tool use, planning, memory, and multi-agent orchestration, using frameworks such as LangGraph, LangChain, AutoGen, or Model Context Protocol (MCP).
- Experience with LLM and agent evaluation, guardrails, and observability, including offline/online evals and hallucination detection.
- Experience optimizing LLM inference for latency and cost (e.g., vLLM, quantization, distillation, GPU serving).
Subsidiary:PayPal
Travel Percent:0
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: ($196,500.00 - $291,500.00 Annually)
Additional Location(s) | Pay Range:No other locations are assigned to this requisition currently.
Additional compensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable.
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.
