End-to-End AI Data Engineer

Mistral Ai; Paris; In loco; EUR 100.000 - 140.000; Tempo pieno

Descrizione del lavoro

Mistral is seeking a Forward Software Engineer, Data to build end-to-end AI systems, from prototype to production, working with data architecture and large‑scale pipelines. You will contribute to retrieval-augmented generation, data governance, and scalable patterns across customer engagements, collaborating with researchers and customer-facing teams.

The role emphasizes ownership, customer impact, and shipping value quickly, with an eye toward production-grade data models and lakehouse-like

Competenze

• Able to ship end-to-end AI systems and software
• 5+ years of experience building and running production data-intensive pipelines
• Experience with retrieval-augmented generation or LLM evaluation
• Independent, able to own problems and outcomes
• Fluent in English and effective communication
• Able to ship incrementally and trade off product-technical decisions

Mansioni

• Build AI systems end to end from prototype to production
• Design data architecture: ingestion, processing, storage, data models/ontologies
• Build distributed pipelines processing large volumes of documents, code, logs, and multimodal content
• Abstract common patterns across customers to scalable platforms
• Ensure systems meet throughput, latency, cost, and failure recovery goals
• Incorporate data governance: ownership, access control, lineage, retention, privacy
• Develop evaluation loop with labelers and versioned eval datasets
• Set standards for data systems design and delivery
• Collaborate with researchers, engineers, and customer-facing teams

Conoscenze

Full stack shipping across the stack (

Strumenti

Neo4j

Descrizione del lavoro

Mistral is seeking a Forward Software Engineer, Data to build end-to-end AI systems, from prototype to production, working with data architecture and large‑scale pipelines. You will contribute to retrieval-augmented generation, data governance, and scalable patterns across customer engagements, collaborating with researchers and customer-facing teams.

The role emphasizes ownership, customer impact, and shipping value quickly, with an eye toward production-grade data models and lakehouse-like