MACHINE LEARNING ENGINEER

• Capitalize on existing algorithms by optimizing them (testing new approaches, etc.) and monitoring them to prevent any drift.

• Deliver new high-value Data Science use cases for new business areas (e.g. Supply Chain, Finance, etc.).

• Develop new Generative/Agentic AI applications with significant business impact.

• Scale use cases to a broader user base and markets.

• Supporting markets on best practices., Within the OMNICHANNEL team, the MACHINE LEARNING ENGINEER will play a pivotal role in the industrialization, deployment, and optimization of Data Science and AI solutions. Working at the intersection of Data Science and engineering, you will ensure the scalability, reliability, and performance of our models and applications, contributing directly to the business impact of AI at our Maison.

• Collaborating closely with Data Scientists and IT teams (LVMH Beauty Tech) to ensure seamless integration of AI applications into production environments (unit tests, CI/CD/CT, DevOps).

• Designing, developing, and maintaining robust and scalable MLOps, LLMops and AgentOps pipelines (mainly on GCP and Dataiku) to automate the deployment, monitoring, and retraining of AI solutions across various data domains.

• Implementing and maintaining advanced monitoring systems to track model and data drift, as well as performance of AI applications (including conversational agents), ensuring their continuous effectiveness.

• Supporting the optimization and refactoring of AI applications (code, Dataiku flows, etc.) to enhance efficiency, scalability, and maintainability.

• Troubleshooting and resolving technical and operational issues related to model deployment and performance.

• Writing clear technical documentation and establishing best practices for model deployment, monitoring, and maintenance.

• Ensuring the security and compliance of deployed AI solutions, including managing access to necessary IT tools and data sources.

• Contributing to the development of demonstrators and prototypes to showcase the value of AI solutions.

• Staying informed of the latest advancements in MLOps, LLMOps, AgentOps and related fields, and proactively proposing innovative approaches to improve our processes and technology stack.

• Drive the Machine Learning Engineering roadmap.

• Sharing knowledge and best practices with Data Science team members at HQ and market levels and supporting their upskilling in MLE areas.

Graduate from a top engineering/computer science school or holder of a PhD with a specialization in AI, MLOps, or Computer Science.

You have significant experience in the Artificial Intelligence area, including at least 2 years in MLOps.

SOFT SKILLS

Excellent communication skills in French and English (working languages), a third language would be an asset.

Strong problem-solving skills.

Creative & Innovative

Critical Thinking

Resourceful

Teamwork & Collaboration

Problem Solving

HARD SKILLS

Strong knowledge of traditional AI (Supervised/Unsupervised Machine Learning, NLP, Deep Learning, Time Series, Computer Vision, etc.).

Strong knowledge of Generative & Agentic AI.

Proficiency in Python (Tensorflow, Sklearn, LangChain, LangGraph, FastApi, Streamlit…) and SQL programming languages.

Proficiency with Google Cloud Platform (and ideally Dataiku); any certification is highly appreciated.

Expertise in MLOps, LLMOps, AgentOps practices (MLFlow, Airflow, Dataiku, Langfuse, LangSmith…).

Expertise in large-scale data processing frameworks and container systems (BigQuery, Docker, GKE).

Expertise in collaborative development platforms and CI/CD/CT methods (Github Actions).

A strategic and demanding role in a dynamic and innovative environment, with opportunities for learning and professional growth.

Projects at the forefront of current trends in Data Science and AI.

Rapid personal development through continuous support and multidisciplinary teams.

A competitive package and career advancement opportunities within the LVMH Group, with a global presence and continuous growth across 75 different Maisons.

ADDITIONAL INFORMATION: ID&E Footing

Inclusivity is not just a noble principle; it is the very heart of our excellence. In a world where our clients, talents, and ideas increasingly come from diverse backgrounds, our diversity is our strength.

At Parfums Christian Dior, this means being a House where everyone feels respected, welcomed, and valued, regardless of their uniqueness. Because we know well: a House that reflects this diversity is a sustainable, vibrant House, rooted in both dreams and reality. Inclusivity cannot be decreed; it is practiced daily.

(If you require any reasonable adjustments within the application process, feel free to indicate it in your application).

Do you wish to join the House of Dreams? In this House, you will continue to perpetuate the dream of our creator: that of a more beautiful and happier world. You will also consolidate our vision: to become the most desirable House in the world of beauty, an absolute reference of French luxury, a symbol of joy and hope. This vision is carried by our six values that you will embody daily as designers of dreams - values that engage and define us: Create Passionately Craft together with joy Excel for ultimate luxury Lead with audacity Cultivate Triumphant inclusivity Commit and act to re-enchant the world Design your dreams with Dior. Parfums Christian Dior is a world-renowned luxury beauty Maison, known for its timeless elegance and innovation. Our commitment to excellence extends to our data practices, and we are seeking a dynamic and experienced Machine Learning Engineer to join our Data Science Team. The impact of data and AI (including Generative AI) is well-established at Dior - key achievements to date: A cutting-edge technology stack (based mainly on GCP, Dataiku, and Python). 20+ algorithms developed to serve 50+ use cases across Client Activation, Retail, Media or e-Commerce (e.g. hyper-targeted and/or personalized customer communications, product recommendations, automated repurchase cycles, anti-churn strategies, high-value prospect identification).