Sr. Machine Learning Engineer

Job Summary

Pay Pal, Inc. seeks Sr. Machine Learning Engineer in San Jose, CA.

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.

• 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.
• 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.

• Experience with large language model (LLM) fine‑tuning, including post‑training optimization methods and dataset, prompt, and evaluation design (6 months).
• Experience with deep learning frameworks:
  PyTorch, and distributed training libraries (Deep Speed, Accelerate, FSDP) (6 months).
• Experience with prompt engineering and prompt optimization: designing effective system, routing, and tool‑calling prompts using reflecting prompting, auto‑prompting, chain‑of‑thought, and augmentation strategies (1 year).
• Experience with agentic framework development: implementing agent workflows using frameworks (CrewAI, Auto Gen, Lang Graph, ReAct, or custom stacks), and understanding memory, planning, orchestration, and tool‑calling patterns (6 months).
• Experience with data engineering for LLMs: data cleaning, synthesis, augmentation, labeling automation, and dataset quality control (1 year).
• 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).
• Production ML systems and MLOps: model deployment, inference optimization, performance monitoring, and scaling using frameworks (vLLM, Ray Serve, Triton, Cosmos) (2 years).
• Experience with API/tooling integration: designing and integrating tool‑calling interfaces, REST APIs, and function schemas for agent workflows, with an understanding of API governance, schema consistency, and tool maturity models (6 months).
• Experience with cloud and compute infrastructure: GPU compute (A100/H100), containerization (Docker), and job orchestration tools (6 months).
• Experience writing clean, scalable, production‑ready code for ML pipelines and agent frameworks using Python, code modularity, testing, debugging, and CI/CD (3 years).

Equal Opportunity Employer (EOE), including disability and veteran considerations.

San Jose, California:
Salary $– per annum. 40 hours per week;
Monday–Friday, 9:00 a.m.–5:00 p.m. Additional compensation may include an annual performance bonus, equity, or other incentive compensation.

Must be legally authorized to work in the U.S. without sponsorship.

Pay Pal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, Pay Pal will provide reasonable accommodations for qualified individuals with disabilities.