Tech Lead AI

Jobtailor; Nantes; Sur place; EUR 90 000 - 130 000; Plein temps

Résumé du poste

Jobtailor in Nantes is seeking a Senior AI Engineer to shape AI architecture, lead a team of AI engineers, and oversee end-to-end deployment of AI use cases for clients. You will drive MLOps practices, maintain code quality, and stay ahead of generative AI innovations.

The role requires 6+ years in AI/data science with leadership experience, strong Python expertise, and cloud platform familiarity (Snowflake, Azure, AWS, GCP). English proficiency is a plus.

Qualifications

• 6+ years in AI engineering or data science, with 2+ years in technical leadership.
• Degree in Computer Science, Data Science, Applied Mathematics or equivalent.
• Proven expertise with LLMs, generative AI and RAG architectures.
• Strong Python skills and ML ecosystem (PyTorch, HuggingFace, LangChain).
• Hands-on MLOps and production deployment (CI/CD, monitoring, orchestration).
• Familiar with cloud/data platforms (Snowflake, Azure, AWS, GCP).
• Excellent ability to communicate complex concepts to business stakeholders.
• Leadership, pedagogical skills, autonomy and team spirit.
• English proficiency is a plus.

Responsabilités

• Define and evolve AI architecture choices across ML, DL, and generative AI.
• Drive technology choices and oversee code reviews and best practices.
• Lead and develop a team of AI Engineers from junior to senior.
• Manage end-to-end production deployment of AI use cases.
• Interact with clients for scoping, reporting, and strategic advisory.

Connaissances

Leadership

Team development

Communication

Autonomy

English proficiency

Formation

Degree in Computer Science, Data Science, Applied Mathematics or equivalent

Outils

Python

PyTorch

HuggingFace

LangChain

MLflow

Airflow

Snowflake

Azure

AWS

GCP

Description du poste

Overview

Define and evolve AI architecture choices: ML, deep learning, generative AI, LLMs; Design robust, scalable AI solutions aligned with business objectives; Ensure the technical quality of deliverables and oversee code reviews; Drive technology choices and maintain active monitoring of AI innovations; Establish engineering best practices (testing, code review, standards); Lead and develop a team of AI Engineers (junior to senior profiles); Structure AI engineering practices: code standards, MLOps, documentation; Contribute to the recruitment and career development of AI profiles within Keyrus; Run technical workshops and share knowledge within the practice; Manage end-to-end production deployment of AI use cases (from POC to production); Design and implement advanced RAG architectures (ingestion, indexing, generation); Optimize GenAI systems (prompt engineering, fine-tuning, evaluation); Implement data pipelines and model monitoring systems; Interact directly with clients: scoping, reporting, strategic advisory; Ensure performance, security, and cost optimization of deployed AI solutions.

Requirements

• Minimum 6 years' experience in AI engineering/data science, including at least 2 years in technical leadership
• Degree in Computer Science, Data Science, Applied Mathematics or equivalent
• Proven expertise with LLMs, generative AI and RAG architectures
• Strong proficiency in Python and the ML ecosystem (PyTorch, HuggingFace, LangChain, etc.)
• Hands-on experience in MLOps and production deployment: CI/CD, orchestration, monitoring (MLflow, Airflow, etc.)
• Familiarity with cloud and data platforms (Snowflake, Azure, AWS, GCP)
• Ability to communicate complex technical concepts to business stakeholders
• Natural leadership, pedagogical skills, ability to develop a team, autonomy and team spirit
• Professional proficiency in English is a plus

ATS Optimization Keywords

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Hard Skills

• AI architecture
• machine learning
• deep learning
• generative AI
• large language models
• Python
• MLOps
• data pipelines
• prompt engineering
• fine-tuning

Soft Skills

• leadership
• team development
• communication
• autonomy
• team spirit
• pedagogical skills
• strategic advisory
• technical workshops
• client interaction
• code review