Postes à Cannes, United States

We’re looking for an AI Engineering Manager to drive the Post-Processing & Evaluation squad of Mirakl’s GenAI-native AI Catalog Transformer. You’ll own the technical vision for improving the quality, reliability, and business impact of GenAI outputs used in catalog enrichment for marketplaces and retailers.

You will manage a team of AI Engineers working at the intersection of AI, software engineering, and business. This team focuses on AI products evaluation and improvements in order to optimize business KPIs.

As AI Engineering Manager, you will:

• Lead, mentor, and grow a cross-functional squad responsible for the post-processing, evaluation, and performance monitoring of GenAI-generated catalog content.
• Manage the technical roadmap and priorities for your team, ensuring alignment with broader organizational goals.
• Design, deploy, and continuously improve model evaluation frameworks and trust-building metrics (such as factual accuracy, hallucination rate, and user perception).
• Build and maintain post-processing components to ensure the clarity, structure, and reliability of GenAI outputs.
• Identify and resolve pain points within the Catalog Transformer; develop and implement monitoring and optimization frameworks.
• Manage the ground truth data pipeline, including annotation workflows and feedback loops, to enable continuous model improvement.
• Develop and maintain internal tooling for Sales, Customer Success, and Support to assess and monitor output quality for each client or use case.
• Engage with stakeholders to define, track, and optimize critical KPIs, and support business teams in data-driven decision-making.
• Collaborate closely with Data Science, Product, and Engineering teams to advance model fine-tuning, transparency, and overall performance.
• Work closely with Engineering Managers and other software squads to promote technical best practices and foster cross-team collaboration.
• Collaborate with pre-sales teams to enable and create proofs of concept for clients.

• Strong skills in model evaluation, post-processing, and data/ML pipelines (Python, SQL, Spark, Airflow)
• Experience building internal tools for enablement or client-facing insights
• Experience with GenAI model evaluation and AI system monitoring
• Experience in AI project production launch and run
• Familiarity with annotation workflows and human-in-the-loop evaluation

• Hands-on technical expertise, with 1–3 years' experience as a Lead or junior Engineering Manager (team management or technical leadership)
• Strong leadership and ability to motivate and unite a technical team
• Very good professional proficiency in English, bilingual a plus
• Adaptability and agility in a fast-paced environment
• Excellent analytical, problem-solving, and strategic thinking abilities
• Results-oriented with a proactive, challenging mindset
• Ability to challenge and support business stakeholders in their thinking and decisions

• Initial phone interview (30 min) with a Tech recruiter: learn about your background, discuss your expectations, and introduce Mirakl
  
  
• Technical interview (1 hour30, video call) with our Senior Data Manager: deep dive into your expertise and experience
  
  
• Values & culture interview (2 rounds of 45 min’) with team members to assess your fit with Mirakl’s culture.

• Shape the AI quality & trust strategy behind one of Mirakl’s most strategic products
  
  
• Connect GenAI performance with business success through smart tooling and evaluation
  
  
• Work at the intersection of AI, Product, and Client Experience in a fast-growing ecosystem
• Shape the development of a Pioneering AI Catalog onboarding tool, being in contact with cutting-edge technologies and technical stacks

Anne-Claire Baschet, Chief Data & AI Officer at Mirakl, discusses the journey from inception to deployment of the Catalog Transformer, highlighting the integration of GenAI into Mirakl's core products.

Fanny Guélin and Arthur Delaitre from Mirakl present at Apidays Paris 2024, discussing the development and scaling of AI products within a SaaS framework, with a focus on the Catalog Transformer.

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