Forward-Deployed AI Engineer: Production-Ready GenAI

Mistral; San Francisco (CA); Vor Ort; USD 140.000 - 190.000; Vollzeit

Zusammenfassung

Mistral AI is seeking an Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges. The role involves working with customers from pre‑sale to post‑implementation to ensure solutions meet expectations.

You will onboard customers on products and APIs, guide prompting and evaluation, and contribute to deployment and production integration across back‑end and front‑end interfaces.

Qualifikationen

• PhD or master’s in AI or data science.
• 2+ years as a technical contributor on AI-based products (data scientist or software engineer).
• Experience in fine-tuning LLMs and in RAG/agentic use cases.
• Strong understanding of ML/LLMs concepts and algorithms.

Aufgaben

• Onboard customers on products and APIs; guide prompting and production integration.
• Work on GenAI applications across industries; drive technological transformation with customers.
• Deploy into production use cases with business impact; collaborate with researchers and product engineers.
• Contribute to open-source codebases; support inference and fine-tuning tasks.
• Engage in pre-sales calls; articulate product capabilities to stakeholders.
• Collaborate with product and science teams to iteratively improve models based on feedback.

Kenntnisse

Python

PyTorch

LLM deployment

Fine-tuning

RAG/agentic use cases

LangChain

Vector databases

Communication

Ausbildung

PhD or Master's in AI/Data Science

Tools

LangChain

VectorDBs

Jobbeschreibung

Mistral AI is seeking an Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges. The role involves working with customers from pre‑sale to post‑implementation to ensure solutions meet expectations.

You will onboard customers on products and APIs, guide prompting and evaluation, and contribute to deployment and production integration across back‑end and front‑end interfaces.