Sr. Machine Learning Engineer

The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy.  We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards.  Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade.  Our beliefs are the foundation for how we conduct business every day.  We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities. Job Summary: Job Description: PayPal, Inc. seeks Sr. Machine Learning Engineer in San Jose, CA  Job Duties: Design and implement machine learning models and AI Agents for a variety of business use cases. Maintain the existing fraud prevention system. Review machine learning models and agents. Work with data engineers to collect, clean, and prepare data for modeling. Develop prototypes and conduct experiments to validate model approaches. Optimize models for performance, accuracy, and scalability in production. Collaborate with software engineers to deploy models into live systems. Communicate technical concepts and results to peers and stakeholders. Stay informed on the latest developments in machine learning and apply them as appropriate. Partial telecommuting permitted from within a commutable distance. Minimum Requirements: Master’s degree, or foreign equivalent, in Computer Science, Control Engineering, or a closely related field, plus three years of experience in the job offered or a related occupation. Employer will accept a Bachelor’s degree, or foreign equivalent, in Computer Science, Control Engineering, or a closely related field, plus five years of experience in the job offered or a related occupation. Special Skill Requirements: 1.           Experience with large language model (LLM) Fine-Tuning, including utilizing post-training optimization methods and designing datasets, prompts, and evaluation methodologies  (6 months); 2.           Experience with Deep Learning Frameworks: PyTorch, and distributed training libraries (DeepSpeed, Accelerate, FSDP) (6 months); 3.           Experience with Prompt Engineering and Prompt Optimization: designing effective system, routing, and tool-calling prompts utilizing reflecting prompting, auto-prompting, chain-of-thought, and augmentation strategies (1 year); 4.           Experience with Agentic Framework Development: implementing agent workflows using frameworks (CrewAI, AutoGen, LangGraph, ReAct, or custom agent stacks), and understanding of memory, planning, orchestration, and tool-calling patterns (6 months); 5.           Experience with data engineering for LLMs: data cleaning, synthesis, augmentation, labeling automation, and dataset quality control  (1 year); 6.           Experience with LLM Evaluation and Experimentation: building offline and online evaluation pipelines, and using A/B testing, simulation-based evaluations, or agentic task benchmarks (1 year); 7.           Production ML Systems and MLOps: model deployment, inference optimization, performance monitoring, and scaling using frameworks (vLLM, Ray Serve, Triton, Cosmos) (2 years); 8.           Experience with API/ Tooling Integration: designing and integrating tool-calling interfaces, REST APIs, and function schemas for agent workflows, utilizing understanding of API governance, schema consistency, and tool maturity models (6 months); 9.           Experience with Cloud and Compute Infrastructure: GPU compute (A100/H100), containerization (Docker), and job orchestration tools (6 months); 10.         Experience with writing clean, scalable, production-ready code for ML pipelines and agent frameworks using the following skills: Python, code modularity, testing, debugging, and CI/CD (3 years). Additional Responsibilities & Preferred Qualifications : EOE, including disability/vets. 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 | Salary: $193,978.00-246,000.00 per annum. 40 hours per week; M-F, 9:00 a.m. to 5:00 p.m. Additional compensation for this role may include an annual performance