ML Engineer: Privacy & Anonymization (Onsite Dublin)

Workday; Dublin; Hybrid; EUR 80,000 - 120,000; Full time

Job summary

Workday is seeking a seasoned Machine Learning Engineer to build and optimize the models and data pipelines behind ogham, our de-identification engine. You will help grow anonymization at scale, collaborating with cross-team partners across Workday’s AI Platform in Dublin.

The role focuses on implementing differential privacy, k-anonymity, l-diversity, and t-closeness, while ensuring privacy-utility balance and policy alignment with legal/compliance teams.

Qualifications

• 5+ years of hands-on experience in Machine Learning Engineering or Data Science (or equivalent research experience via a Ph.D.).
• Proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow.
• Data pipelines: building and operating large-scale data processing pipelines using Spark or equivalent distributed frameworks.
• Cloud & Production: deploying, scaling, and maintaining ML systems in production on AWS (or equivalent cloud platform).
• Education: Bachelor’s degree in Computer Science, Physics, Mathematics, or a related quantitative field (or equivalent practical experience).

Responsibilities

• Anonymization & Privacy Engineering: Apply and evaluate privacy techniques across real enterprise use cases, measuring the privacy-utility trade-off and turning findings into actionable recommendations for data governance.

Skills

Python

PyTorch

TensorFlow

Spark

AWS

Machine Learning

Education

Bachelor's degree in Computer Science, Physics, Mathematics, or related field

Tools

EMR

SageMaker

Spark

Job description

Workday is seeking a seasoned Machine Learning Engineer to build and optimize the models and data pipelines behind ogham, our de-identification engine. You will help grow anonymization at scale, collaborating with cross-team partners across Workday’s AI Platform in Dublin.

The role focuses on implementing differential privacy, k-anonymity, l-diversity, and t-closeness, while ensuring privacy-utility balance and policy alignment with legal/compliance teams.