- Company Name
- KatchMe
- Job Title
- Référent IA (Lead ML) - IA generative - Paris
- Job Description
-
**Job title**
AI Lead (ML Lead) – Generative AI
**Role Summary**
Lead the design, development, and production of generative AI capabilities for a SaaS retail solution. Own the technical vision, build scalable ML pipelines, drive research on Retrieval-Augmented Generation (RAG) and large language model (LLM) orchestration, and mentor a small engineering team.
**Expectations**
- 7+ years of experience in machine learning, NLP, or LLMs with a track record in production SaaS environments.
- Proven expertise in RAG, LLMOps, agent orchestration (LangChain, LangGraph).
- Strong Python programming and understanding of backend/data architecture.
- Experience with CI/CD, monitoring, and performance tuning for ML models.
- Technical leadership: coaching, code reviews, hiring, and process definition.
- Passion for applying AI to real business problems and a pragmatic, curious mindset.
**Key Responsibilities**
- Define and steward the AI strategy and technical roadmap (RAG, semantic search, LLMs).
- Architect and industrialize end‑to‑end AI pipelines: ingestion, vectorization, indexing, fine‑tuning, evaluation, monitoring.
- Ensure robustness, scalability, and security of AI components in partnership with platform/backend teams.
- Mentor, pair‑program, conduct code reviews, set best‑practice guidelines, and recruit team members.
- Lead algorithmic research and prototype new models to improve assistive copilote accuracy and relevance.
- Oversee deployment pipelines, CI/CD, and performance monitoring (e.g., Langfuse, DVC).
- Collaborate with product and engineering squads to translate business requirements into AI solutions.
**Required Skills**
- Python, Docker, Git, FastAPI.
- ML/NLP frameworks: HuggingFace, LangChain, LangGraph, Sentence Transformers, LLMOps tooling.
- Vector store & graph databases: Qdrant, Neo4j.
- Cloud: Google Cloud Platform, BigQuery, Cloud Storage, API integration.
- Model deployment & monitoring: Langfuse, DVC, CI/CD pipelines.
- Experience with RAG, semantic search, and agent orchestration.
- Leadership: mentoring, code review, hiring, process improvement.
- Strong analytical, problem‑solving, and communication skills.
**Required Education & Certifications**
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related field.
- Certifications in ML/NLP (e.g., TensorFlow, PyTorch, GCP ML Engineer) are advantageous.