Staff AI Engineer

ManoMano

Staff AI Engineer developing LLM, retrieval, agentic AI, and recommendation features. Scaling AI products for ManoMano’s online DIY and home-improvement marketplace in Paris.

Posted 8/9/2026full-timeParis • 🇫🇷 FranceLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing AI solutions using LLMs and retrieval-augmented generation, with a strong focus on building reliable information retrieval pipelines and orchestrating agentic AI systems. Proficient in coding, evaluation metrics, and collaboration with cross-functional teams to drive product-aligned outcomes.

Highest-signal resume keywords

Machine LearningDeep LearningLLM Application DevelopmentInformation RetrievalPython

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Hard Skills

Machine LearningDeep LearningLLM Application DevelopmentInformation RetrievalHybrid SearchVector DatabasesRAG ArchitecturesProduction-Ready CodeA/B TestingEvaluation Metrics

Soft Skills

Proficient Communication SkillsAnalytical SkillsUser-Focused MindsetResult-Oriented ApproachGrowth Mindset

Tools & Technologies

W&BMLFlowDaskRaySpark

Industry Keywords

E-CommerceB2C MarketplaceRecommendation SystemsPersonalizationCausal Inference

Tech Stack

Tools & technologies

PythonRaySparkSQL

About the role

Key responsibilities & impact

Design and implement AI solutions using LLMs, retrieval-augmented generation (RAG), and agentic frameworks
Build and maintain information retrieval pipelines, including hybrid search, vector databases, and multi-stage re-ranking systems
Develop and fine-tune LLM and vision-language models for product categorization, attribute extraction, and semantic search
Build and orchestrate agentic AI systems interacting with internal tools and external data sources
Write production-ready code and deploy AI systems at scale
Define and track evaluation metrics, run A/B tests and benchmarks, and communicate results
Partner with software engineers, product managers, and business stakeholders to frame problems
Investigate and fix production issues and ensure reliability, observability, and performance
Stay engaged with the latest AI trends, including Generative AI, agentic systems, and scalable ML

Requirements

What you’ll need

5 to 10 years of experience in Machine Learning, Deep Learning, or AI Engineering, including taking models from prototype to production at scale
Hands-on experience with LLM/VLM application development, including fine-tuning, prompt engineering, tool use, evaluation, and benchmarking
Experience with information retrieval, hybrid search, large-scale embeddings, vector databases, and RAG architectures
Experience building or orchestrating agentic AI systems
Ability to design product-aligned metrics, run controlled experiments, and communicate results
Experience with large-scale production applications, including monitoring, reliability, performance, and observability
Strong coding skills in Python and proficiency in SQL
Proficient oral and written communication skills in English
User-focused mindset, strong analytical skills, and result-oriented approach
Growth mindset
Nice to have: e-commerce or B2C marketplace experience
Nice to have: familiarity with W&B, MLFlow, Braintrust, and MLOps practices
Nice to have: scalable processing frameworks such as Dask, Ray, or Spark
Nice to have: Bayesian inference and causal inference familiarity
Nice to have: recommendation systems and personalization knowledge

Benefits

Comp & perks

Part-time remote option (max 2 days per week)
Flexible working hours
Health care coverage
Meal Voucher: Swile Card
Employee discount on our DIY & HI offering
Mental health support with moka.care
Free access to a gym in Paris