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Staff Machine Learning Engineer at PayPal
Dublin, Leinster, Ireland -
Full Time

Start Date

Immediate

Expiry Date

18 Feb, 26

Salary

0.0

Posted On

20 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Machine Learning, Data Engineering, Python, SQL, ML Libraries, Exploratory Data Analysis, Feature Engineering, Data Integrity, Fairness, Explainability, Root Cause Analysis, Anomaly Detection, Communication Skills, Collaboration, Problem Solving, Statistical Models

Industry

Software Development

Description
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.
Responsibilities
Partner with product and platform engineering teams to build scalable ML-based products. Oversee the development and maintenance of production-level data pipelines and machine learning algorithms.