Hybrid ML Engineer: Privacy‑Driven De-identification

The available sources do not contain information about the company name for rounx.com.; Ireland; Hybrid; EUR 80,000 - 120,000; Full time

Job summary

Danu, part of Workday’s AI Centre of Excellence in Dublin, is seeking a Machine Learning Engineer to build and refine models and data pipelines for ogham, our de-identification engine with broader anonymization ambitions.

The role focuses on privacy techniques like differential privacy and k-anonymity, evaluates effectiveness, and collaborates with legal, compliance and product teams to ensure scalable, reliable ML systems. You will own model optimization and pipeline ownership end-to-end.

Qualifications

• 5+ years of experience in ML engineering or data science.
• Proficiency in Python and ML frameworks (PyTorch/TensorFlow).
• Experience with large-scale data pipelines using Spark or similar tools.
• Familiarity with AWS.
• Knowledge of privacy techniques (differential privacy, k-anonymity).
• Ability to communicate clearly across legal, compliance and product teams.

Responsibilities

• Build and refine ML models and data pipelines for ogham, the de-identification engine.
• Model optimization and pipeline ownership.
• Collaborate with cross-functional teams to ensure scalable and reliable ML systems.

Skills

Python

PyTorch

TensorFlow

Spark

Tools

AWS

Job description

Danu, part of Workday’s AI Centre of Excellence in Dublin, is seeking a Machine Learning Engineer to build and refine models and data pipelines for ogham, our de-identification engine with broader anonymization ambitions.

The role focuses on privacy techniques like differential privacy and k-anonymity, evaluates effectiveness, and collaborates with legal, compliance and product teams to ensure scalable, reliable ML systems. You will own model optimization and pipeline ownership end-to-end.