Machine Learning Engineer

Position: Staff Machine Learning Engineer
The Company
Pay Pal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, Pay Pal 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. Pay Pal 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 Pay Pal or Venmo account balance, Pay Pal 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 Pay Pal, 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 Description

Summary:

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.

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 Tensor Flow, PyTorch, or scikit-learn.
Expertise in cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.

Additional Responsibilities And

Preferred Qualifications
Experience owning end-to-end ML model life cycles, including training, evaluation, deployment, monitoring, and retraining in production environments.
Strong hands-on experience with MLOps best practices and platforms, such as experiment tracking, model versioning, and automated training/deployment pipelines (e.g., MLflow, Kubeflow, Airflow, Sage Maker, Vertex AI).
Experience building and scaling LLM- and GenAI-based systems, including fine-tuning, inference optimisation, prompt management, and retrieval-augmented generation (RAG) pipelines.
Proven ability to design scalable, reliable, and cost-efficient ML inference systems, with familiarity in containerisation, orchestration, and infrastructure-as-code (Docker, Kubernetes, Terraform).

Experience with large-scale data processing and distributed systems (e.g., Spark) and integrating ML solutions into complex production architectures.
Understanding of Responsible AI practices (explainability, fairness, robustness, compliance) and demonstrated technical leadership or mentorship influencing ML architecture and standards.

Pay Pal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. Any such request is a red flag and likely part of a scam. To learn more about how to identify and avoid recruitment fraud please visit

For the majority of employees, Pay Pal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of…