ML Engineer: Anonymization & Privacy at Scale

Workday; Dublin; On-site; EUR 80,000 - 120,000; Full time

Job summary

Workday’s Dublin AI Centre of Excellence is seeking an experienced Machine Learning Engineer to build and optimize de-identification and anonymization capabilities that protect sensitive data across Workday’s AI systems. You will work with cross‑functional teams to deploy scalable ML solutions and ensure privacy compliance in production environments.

You will lead model improvements, manage end-to-end data pipelines, and collaborate with legal and product teams to implement governance standards

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 ML frameworks such as PyTorch or TensorFlow.
• Proven experience building and operating large-scale data processing pipelines using Spark or equivalent distributed frameworks.
• Hands-on experience deploying, scaling, and maintaining ML systems in production on AWS (or equivalent cloud platform).
• 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.
• Model Optimization & Fine-Tuning: Build, fine-tune, and continuously improve de-identification and anonymization models — including Named-Entity Recognition (NER) and pattern-matching layers — balancing accuracy, latency, and compute efficiency.
• Pipeline Ownership & Operations: Own the full lifecycle of data exploration, transformation, feature and prompt engineering, and model design across high-throughput Spark, EMR, and SageMaker batch pipelines, and support these pipelines in production, diagnosing issues such as memory errors and capacity constraints.
• Cross-Functional Collaboration: Partner with platform, infrastructure, and product engineering teams to translate requirements into reliable, scalable ML systems, and collaborate alongside legal and compliance stakeholders to implement data governance frameworks.
• Technical Communication: Act as a point of contact for cross-team questions about de-identification behavior, communicating results and architectural decisions clearly in writing for technical, legal, and customer-facing audiences.

Skills

Python

PyTorch

TensorFlow

Spark

AWS

NLP

NER

Differential Privacy

GDPR/Privacy

Communication

Education

Bachelor's degree in Computer Science, Physics, Mathematics

Tools

SageMaker

EMR

Hugging Face

Spark

Job description

Workday’s Dublin AI Centre of Excellence is seeking an experienced Machine Learning Engineer to build and optimize de-identification and anonymization capabilities that protect sensitive data across Workday’s AI systems. You will work with cross‑functional teams to deploy scalable ML solutions and ensure privacy compliance in production environments.

You will lead model improvements, manage end-to-end data pipelines, and collaborate with legal and product teams to implement governance standards