Generative AI Engineer: Build Scalable LLMs

Aramisauto; Arcueil; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

Aramis Group is seeking an AI/ML Engineer specialised in Generative AI to build and scale LLM capabilities across the Group. You will join a young, multidisciplinary data team focused on high-impact use cases for customers and employees.

You’ll design, deploy conversational AI agents, work on voice-based use cases, integrate LLMs, APIs, vector databases and RAG architectures, and build robust data and AI pipelines using Python, SQL, Docker and cloud tech.

Qualifications

• Degree in data science, ML, statistics, econometrics, CS or related field, or equivalent experience.
• Several years of experience in AI/ML engineering, with hands-on production deployments.
• Strong foundations in Python, SQL and Docker and solid ML/DL concepts.
• Practical experience with LLMs, prompt engineering, RAG architectures, vector databases or conversational AI.

Responsabilités

• Build and deploy Generative AI solutions to improve customer interactions.
• Develop reliable, scalable, production-ready LLM applications for Aramis Group across Europe.
• Explore new AI approaches, assess value, share learnings with the team.
• Contribute to continuous improvement of AI products from experimentation to production monitoring.

Connaissances

Python

SQL

Docker

LangChain

Hugging Face

FastAPI

OpenAI API

Anthropic Claude

Google Vertex AI

RAG

Pinecone

Weaviate

pgvector

Whisper

Elasticsearch

Kibana

Snowflake

AWS

GitLab elevenlabs

Formation

Degree in data science / machine learning / statistics / econometrics / CS or related field

Outils

LangChain

Hugging Face

OpenAI API

Anthropic Claude

Google Vertex AI

Pinecone

Weaviate

pgvector

Description du poste

Aramis Group is seeking an AI/ML Engineer specialised in Generative AI to build and scale LLM capabilities across the Group. You will join a young, multidisciplinary data team focused on high-impact use cases for customers and employees.

You’ll design, deploy conversational AI agents, work on voice-based use cases, integrate LLMs, APIs, vector databases and RAG architectures, and build robust data and AI pipelines using Python, SQL, Docker and cloud tech.