Staff Machine Learning Engineer

PayPal • San Jose, CA

6d • Hybrid

About The Position

This job will lead the design, development, and implementation of advanced machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences.

Requirements

• 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.

Nice To Haves

• Experience with AI or agentic systems, including exposure to LLM-based agents, autonomous decision-making components, or multi-agent workflows; ability to integrate or operationalize these capabilities within data or ML solutions.
• Research experience in ML/AI areas with publications or open-source contributions a plus
• Experience with transformer-based architectures (e.g., BERT, GPT, T5), including fine-tuning and domain adaptation
• Knowledge of reinforcement learning, including policy optimization, value function approximation, or bandit algorithms
• Hands-on experience with graph-based models (e.g., GCN, GraphSAGE, GAT) or graph representation learning
• Experience with semi-supervised, self-supervised, or unsupervised representation learning
• Knowledge of causal inference, anomaly detection, and incremental/continual learning
• Exposure to synthetic data generation techniques for model training or evaluation
• Prior work in fraud detection, risk modeling, or other high-impact, high-noise domains

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.

Benefits

• medical, dental, vision, life and disability insurance, parental and family leave, 401(k) savings plan, paid time off, and other benefits
• flexible work environment
• employee shares options
• health and life insurance

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees