Staff Machine Learning Engineer jobs at Paypal in Ireland, Dublin

This job will design, develop, and implement 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.

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.

Expected 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.

Our Benefits:

Any general requests for consideration of your skills, please

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.

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.

Expected Qualifications:

• 5+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.

Our Benefits:

Any general requests for consideration of your skills, please

You will be joining the Global Fraud Prevention organization to create and establish the Red Team capability - a groundbreaking function that operates at the intersection of offensive security and fraud research.

Technical Execution:

• Plan and execute red team engagements simulating real-world fraud attacks to expose gaps in fraud detection and prevention systems.
• Develop and deploy fraud attack simulations, including account takeover scenarios, synthetic identity fraud, payment manipulation, and automated bot attacks. You will collaborate closely with fraud operations, data science teams, and InfoSec to develop purple team strategies that continuously refine both offensive techniques and defensive capabilities.
• Conduct research on fraudsters' toolkits, malware, and automated fraud tools used against PayPal and its affiliates, analyzing network traffic patterns and behavioral indicators associated with fraud

What You Need to Bring

Required:

• 6+ years of experience in offensive security, cybercrime, cyber-fraud, or related areas
• Demonstrated experience building security capabilities or teams from inception
• Leadership experience coordinating technical activities and influencing cross-functional stakeholders
• Experience conducting red team engagements with fraud-related techniques (account manipulation, payment fraud simulation, data exfiltration)
• Proficiency in attack automation and tool development
• In-depth familiarity with the cybercrime and cyber-fraud environment
• Proficiency in multiple programming languages and both Linux and Windows environments
• Strategic thinking and entrepreneurial mindset

Preferred:

• Published security or fraud research (tools, papers, exploit analysis)
• Experience as a founding member or early hire in security teams
• Knowledge of network protocols, traffic analysis, and fraud detection technologies (SIEM, EDR, anti-fraud engines)
• Experience with big data platforms (Splunk, Hadoop) and machine learning approaches to fraud detection
• Knowledge of payment systems, digital wallets, and e-commerce fraud vectors
• Industry certifications (OSCP, OSCE, GPEN, GXPN)
• Track record of influencing security strategy at the organizational level

Our Benefits:

Any general requests for consideration of your skills, please

We're part of Global Fraud Prevention team, dedicated to building foundational data infrastructure, automation, and ML tooling that enhance risk decisioning at scale. We're seeking a senior machine learning engineer with strong interest in payment industry to lead data-driven initiatives that improve fraud detection and prevention. In this role you will design and implement scalable machine learning data pipelines, ensure high data quality and integrity, develop and deploy production grade solutions, and provide mentorship to junior team members. Your work will directly contribute to smarter, faster, and more reliable risk decisions across our global platform.

Essential Responsibilities:

• Design and implement holistic and data-driven solutions to support Paypal’s global financial and fraud risk objectives.
• Partner with product and platform engineering teams to build cutting-edge, scalable, and secure ML-based products that enhance global customer experiences.
• Collaborate closely with data engineering and analytics teams to ensure reliable, high-quality training data and robust monitoring infrastructure.
• Oversee the development and maintenance of production-level data pipelines, machine learning algorithms, and advanced statistical models.
• Utilize large-scale datasets to perform exploratory data analysis and feature engineering to drive strategic business decisions.
• Ensure data integrity, fairness, and explainability in deployed machine learning systems through rigorous testing, validation, and bias detection practices.
• Communicate business insights and progress updates effectively to stakeholders and senior leadership through clear visualizations and narratives.
• Lead, mentor, and grow a team of data scientists and ML engineers, fostering innovation in machine learning techniques such as supervised learning, unsupervised learning, reinforcement learning, and deep learning.

• 8+ years of work experience in relevant positions (e.g. data scientist, data analyst, statistician, decision scientist, FP&A, product/process manager, risk management, army intelligence units) domains.
• Strong proficiency in Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow).
• Experience with LLMs, prompt engineering, RAG pipelines, or AI agents is a strong plus.
• Deep understanding of root cause analysis, anomaly detection, or incident forensics.
• Proven ability to translate business problems into data science solutions.
• Excellent communication skills and a collaborative mindset.
• Quick-thinker, fast learner, wide general knowledge, problem solver
• Bachelor’s or Master’s in Computer Science, Statistics, Engineering, or related field. PhD a plus.

Belonging at PayPal:

Any general requests for consideration of your skills, please

This job will oversee the strategic direction and execution of machine learning projects. 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.

Essential Responsibilities:

• Define and drive the strategic vision for machine learning initiatives within the team.
• Lead the development and optimization of 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.
• Mentor and guide junior engineers and data scientists.
• Ensure adherence to best practices and industry standards in ML development.

Expected Qualifications:

• 8+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
• Experience leading others

Our Benefits:

Any general requests for consideration of your skills, please

In this job you will design, develop, and implement 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.

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.

Expected 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.

Our Benefits:

Any general requests for consideration of your skills, please

This job will design, develop, and implement 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.

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:

• Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent 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.

Preferred Qualification:

• MSc or equivalent experience in a quantitative field (Computer Science, Mathematics, Engineering, Artificial Intelligence, etc.) or a bachelor's degree in engineering, science, statistics or mathematics with a strong technical background in machine learning.
• Hands-on experience with Python or Java, along with relevant technologies such as Spark, Hadoop, Big-Query, SQL, is required.
• Candidates must possess a comprehensive understanding of machine learning algorithms and explainable AI techniques. Additionally, expertise in at least one of the following specialized areas is required: Computer Vision, Graph Mining, Natural Language Processing (NLP), or Generative AI (GenAI).
• Experience with Cloud frameworks such as GCP, AWS is preferred.
• Experience withdeveloping machine learning modelsat scale from inception to business impact
• Experience in designing ML pipelines, including model versioning, model deployment, model testing, and monitoring
• Experience in mentoring and supporting junior data scientists or engineers.
• Experience working in a multi-cultural and multi-location organization – an advantage.
• Team player, responsible, delivery-oriented, details-oriented, outstanding communication skills.

Our Benefits:

Any general requests for consideration of your skills, please