ML Engineer: Fairness & Privacy in Trusted AI Pipelines

Inria Villeneuve d'Ascq; Villeneuve-d'Ascq; On-site; EUR 52,000 - 70,000; Full time

Job summary

Inria Villeneuve d'Ascq is seeking an engineer to advance fairness and privacy-preserving ML in the MAGNET team. You will help expand FairGrad, benchmark integrations with scikit-learn and related libraries, and implement pipelines that learn from locally private data.

Based in Lille, you will work under the supervision of Michaël Perrot and collaborate with the ML community to make fairness and privacy techniques accessible and practical.

Qualifications

• Proficient in English, both written and spoken.
• Strong Python programming skills and hands-on implementation experience.
• Solid background in mathematics and statistical methods.
• Good knowledge of machine learning, statistics, and algorithms.
• Familiarity with fairness and privacy topics is a plus.

Responsibilities

• Review and follow existing libraries on Fairness and Privacy preserving ML.
• Maintain, benchmark and expand the FairGrad library.
• Implement, maintain, and benchmark ML pipelines using locally private data.

Skills

English

Python

Implementation

Mathematics

Machine Learning

Statistics

Algorithms

Fairness knowledge

Tools

FairGrad

scikit-learn

AIF360

Fairlearn

NumPy

Job description

Inria Villeneuve d'Ascq is seeking an engineer to advance fairness and privacy-preserving ML in the MAGNET team. You will help expand FairGrad, benchmark integrations with scikit-learn and related libraries, and implement pipelines that learn from locally private data.

Based in Lille, you will work under the supervision of Michaël Perrot and collaborate with the ML community to make fairness and privacy techniques accessible and practical.