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Sr Machine Learning Engineer

paypal -
Dublin, County Dublin

Apply Now

Job details

Full-time

Benefits

Annual leave

Qualifications

TensorFlow
Azure
Go
Law
Spark
Google Cloud Platform
Java
Master's degree
SQL
AWS
Analysis skills
Bachelor's degree
Distributed systems
Scala
Data analytics
GitHub
Kafka
Business requirements
AI
Communication skills
Python

Full job description

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:

We are part of PayPal’s Global Fraud Prevention organization, focused on building automation, tools, and infrastructure that enhance risk decisioning at scale. We are seeking a senior-level Machine Learning Data Scientist & Engineer with deep analytical expertise and a passion for payments. In this role, you will transform complex data into actionable insights, design and deploy advanced models, and contribute to strategic decision-making across the business. You will lead end-to-end data science initiatives - from data mining and feature engineering to model development and operationalization - while partnering closely with product, engineering, and analytics stakeholders. This position is ideal for someone who thrives in a dynamic environment, enjoys solving complex problems, and is motivated by delivering meaningful business impact.

Job Description:

Essential Responsibilities:

Develop and optimize machine learning models for various applications.
Preprocess and analyze large datasets to extract meaningful insights.
Deploy ML solutions into production environments using appropriate tools and frameworks.
Collaborate with cross-functional teams to integrate ML models into products and services.
Monitor and evaluate the performance of deployed models.

Minimum Qualifications:

3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
Several years of experience in designing, implementing, and deploying machine learning models.

Additional Responsibilities & Preferred Qualifications:

Additional Responsibilities

Experience designing and supporting large-scale data platforms, distributed systems, and production-grade data pipelines.
Experience applying data analytics, statistical modeling, and machine learning techniques to fraud detection, risk management, or related domains.
Hands-on experience leveraging AI-assisted development tools such as Claude, Cursor, GitHub Copilot, ChatGPT Enterprise, Gemini, or similar platforms to improve engineering productivity.
Experience with cloud platforms such as GCP, AWS, or Azure.
Working knowledge of data integration, ETL/ELT frameworks, data governance, data quality, metadata management, and monitoring.
Strong programming skills in Python and SQL. Experience with Spark/PySpark, Java, Scala, or Go is a plus.
Strong analytical, problem-solving, and communication skills with the ability to work effectively in a collaborative environment.
Collaborate with Product and Engineering teams to build scalable machine learning-powered products that improve customer experience and business outcomes.
Partner with Data Engineering, Analytics, and Platform teams to develop reliable datasets, feature pipelines, and monitoring solutions.
Analyze large-scale datasets to perform feature engineering, anomaly detection, and identify emerging fraud trends and business opportunities.
Develop and optimize risk models, rules, and mitigation strategies using data-driven experimentation and machine learning techniques.
Contribute to modern data architecture and scalable data processing solutions for high-volume transaction systems.
Communicate technical findings and recommendations clearly to cross-functional partners and stakeholders.
Contribute to engineering best practices through documentation, code reviews, and knowledge sharing.

Preferred Qualifications

5+ years of experience in Data Engineering, Data Science, Machine Learning Engineering, Fraud Analytics, Risk Modeling, or related disciplines.
Experience building AI-powered applications, LLM-based solutions, prompt engineering workflows, or Retrieval-Augmented Generation (RAG) applications.
Familiarity with Agentic AI frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, or similar technologies.
Experience with modern data platforms including Spark, Kafka, BigQuery, Snowflake, Databricks, or other cloud-native analytics platforms.
Familiarity with MLOps, LLMOps, feature stores, experiment tracking, model governance, and production monitoring.
Ability to translate business requirements into scalable data and machine learning solutions.
Strong collaboration and communication skills with the ability to work effectively across cross-functional teams.

Subsidiary:

PayPal

Travel Percent:

PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. When making an application directly, we will never ask you to share passwords, one-time passcodes (OTP), or verification codes. Any such request is a red flag and likely part of a scam. All communication regarding your application will come from official PayPal email domains. If you suspect fraudulent activity, please report it immediately. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact-us.

For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.

Our Benefits:

At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset-you. That’s why we offer comprehensive, choice-based programs, to support all aspects of personal wellbeing—physical, emotional, and financial—delivering meaningful value where it matters most. We strive to create a flexible, balanced work culture with a holistic approach to benefits, including generous paid time off, healthcare coverage for you and your family, and resources to create financial security and support your mental health.

Who We Are:

Commitment to Diversity and Inclusion

PayPal 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, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at [email protected].

Belonging at PayPal:

Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal.

Any general requests for consideration of your skills, please Join our Talent Community.

We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply.

Apply Now

Refine Your Search

learning media developer, data center learning jobs in santry, d

Sr Machine Learning Engineer

Director of Software Engineering - Workplace Technology

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