Product Manager - ML & GenAI Foundations (AI Platform) - Freelance (M/F)

CONTEXT

Within the AI Platform team, you will be the guarantor of the fundamental technological foundations enabling the acceleration and industrialization of classical Machine Learning and Generative AI use cases within a large company.

Your product scope is built around two major pillars:

ML Foundations Scope:

• Industrialization and ML project templates (ML templates, Databricks ML Runtime environments).
• Traceability, monitoring, and model lifecycle management (MLflow).
• Management and provision of specialized infrastructure resources (GPUs, InsightML zone).

GenAI Foundations Scope:

• Enterprise-scale LLM access and serving (LLM access/serving, multi-cloud integration via AWS Bedrock, GCP Vertex AI, Databricks Foundation Models/LLMs).
• Unified and secure access point via our AI Gateways.
• Rapid experimentation tools for teams (e.g., our GET IT LLM access test service).
• Consumption of GenAI services & APIs, and ensuring Governance (security, costs, compliance, data sovereignty).

Main users: Data Scientists, ML Engineers, and developers seeking high-performance, stable, standardized tools and direct self-service access to the best models on the market.

Examples of current challenges:

• How to simplify and standardize the production deployment of ML models (from experimentation on MLflow to deployment)?
• How to offer secure, governed, and scalable access to LLMs (via AI Gateways / Bedrock / Vertex AI) while controlling costs and governance?
• How to allow business and technical teams to quickly test new GenAI hypotheses using tools like GET IT?
• What strategy to adopt to optimize and arbitrate GPU resource allocation for our users?

MISSIONS

As Product Manager - ML & GenAI Foundations, you will apply a product-oriented approach for our internal technical teams:

• Write and champion the product vision for ML & GenAI foundations, understanding market state-of-the-art and user needs.
• Co-construct the roadmap, prioritize the Product Backlog, and manage the product budget in partnership with the technical team leader.
• Be the voice of Data Scientists and Developers, translating their challenges into features and providing them with direction.
• Facilitate tool adoption (demos, documentation, governance guidelines, training, and feedback loops).
• Define and drive KPIs for performance, stability, adoption, and cost efficiency of AI infrastructures.
• Work in synergy with the Group Product Manager Data Factory and other platform pillars to ensure global consistency.

TECHNICAL STACK & ECOSYSTEM

• ML Foundations: MLflow, Databricks ML Runtime, GPUs, ML Templates, InsightML.
• GenAI Foundations: AWS Bedrock, GCP Vertex AI, Databricks FM/LLMs, AI Gateways, GET IT, GenAI APIs.
• Lakehouse & Data: Databricks, Spark, Python.
• Ops & Infra: Terraform, Kubernetes.
• Product Management: Jira Product Discovery, GitHub, Confluence.

1. Solid technical understanding of the modern AI/ML ecosystem (ML lifecycle, fine-tuning/prompting, LLM architectures, GPU management, API Gateway and governance issues)
2. Experience interacting with a highly technical population (Data Scientists, ML Engineers, Cloud Architects) while knowing how to simplify concepts and prioritize based on business value
3. Natural integration of scalability, security, cost control (FinOps), and performance issues into the roadmap
4. User orientation, rigor, and a strong sense of service
5. Proficiency in English, both spoken and written (B2 level required)
6. Thirst for challenges and a desire to learn