Sr Machine Learning Engineer

PayPal

Hybrid

Quick summary

Work type
Hybrid
Location
San Jose, CA
Salary
$159,500–$236,500 / yr
Posted
68 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $216k
This role $198k
$147k most similar roles pay here $273k

This role pays less than 63% of similar roles. Most pay $181,397–$249,750 — the shaded band above. At the midpoint, this role pays about $198k versus about $216k for comparable roles.

Based on 240 similar postings.

Employer

About PayPal

PayPal is a leading global digital wallet and online payment system, founded in 1998, that allows individuals and businesses to send, receive, and manage funds securely in over 200 markets.

PayPal currently has 84 open roles on FindRole.

Listed pay typically runs $160,500–$235,826 across 84 roles with salary data.

Most-posted roles

View all roles at PayPal

At a glance

TL;DR · Sr Machine Learning Engineer

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As a Senior Machine Learning Engineer on the PayPal team, you will design and develop advanced machine learning models to address complex business challenges. Your daily tasks include translating research ideas into production-ready systems using Python, with expertise in agentic frameworks like LangChain or custom orchestration systems. You will work extensively with large language model APIs, implementing tool-use patterns such as function calling and prompt engineering at scale. Additionally, you must have a deep understanding of evaluation methodologies for AI systems beyond academic benchmarks, focusing on practical metrics like safety and task completion under adversarial conditions. Ideal candidates hold a PhD in relevant fields and possess strong engineering skills to build robust, scalable solutions.

Skills

Python LangChain Google_ADK LLM_APIs function_calling structured_outputs retrieval_augmented_generation chain_of_thought prompt_engineering evaluation_methodology AI_system_performance_metrics safety hallucination_rates task_completion_adversarial_conditions

What you'll do

  • Design and develop machine learning models to solve complex problems.
  • Implement advanced algorithms for large language model agents and multi-agent systems.
  • Build production-ready systems using agentic frameworks like LangChain or custom architectures.
  • Utilize LLM APIs effectively, focusing on function calling and prompt engineering at scale.
  • Evaluate AI system performance beyond academic benchmarks, including safety and adversarial conditions.

What we're looking for

  • PhD in Computer Science, AI/ML, NLP, or related field with relevant research experience.
  • Expertise in converting research ideas into production systems using Python.
  • Proficiency in agentic frameworks like LangChain and Google ADK, understanding trade-offs.
  • Experience with LLM APIs, tool-use patterns, and prompt engineering at scale.
  • Knowledge of evaluation methodologies for AI systems beyond academic benchmarks.

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