In less than a decade, ManoMano has become a key player in the home improvement and renovation sector.

Launched in 2013, ManoMano is the reference online marketplace for DIY, home improvement and gardening. Co-founded by Philippe de Chanville and Christian Raisson, ManoMano brings together the largest offer of DIY & gardening online products: electricity, plumbing, hardware, frames, indoor and outdoor furniture, tools, etc. With more than 5 000 seller partners and 11 million products, ManoMano currently employs 500 people and operates in 6 markets (France, Belgium, Spain, Italy, Germany, United Kingdom).

Motivated by the prospect of improving the living environment of their customers and convinced of the importance of the home market for sustainable consumption habits, the ManoMano teams want to help write a new page in their industry, which is struggling to reform itself. ManoMano brings to a highly technical world the power of its sector expertise, combined with that of data and digital in all its dimensions, to offer our customers easy access to innovative advice, products and services 100% online.

The ambition of the Founders and, above all, of Manas & Manos? To accompany this sector transformation with a strong culture of boldness, in an ingenious and frugal organization that places people and teams at the heart of the company's development.


Team & Context

The Machine Learning team is an applied ML team of 14 people with a strong focus on delivery. We are outcome-oriented: we solve high-impact business problems and strive to deliver value to our customers.

We are seeking an AI Engineer for our Paris office to join a team of ML practitioners building the next generation of AI-powered features across our marketplace. You will work on high-impact challenges, including LLM-powered catalog enrichment and attribute extraction, intelligent search and information retrieval, agentic AI systems, and recommendation systems.

The ML team is instrumental in the growth of ManoMano and is now fully committed to building AI and ML products on our marketplace. You will be at the forefront of that transformation, designing, deploying, and iterating on AI solutions at scale.

Your Responsibilities

- Design and implement AI solutions leveraging Large Language Models (LLMs), retrieval-augmented generation (RAG), and agentic frameworks to solve complex business problems.

- Build and maintain information retrieval pipelines, including hybrid search (sparse + dense), vector databases, and multi-stage re-ranking systems.

- Develop and fine-tune LLM and vision-language models (VLMs) for domain-specific tasks such as product categorization, attribute extraction, and semantic search.

- Build and orchestrate agentic AI systems that interact with internal tools and external data sources.

- Write production-ready code and deploy AI systems in a live environment at scale.

- Define and track evaluation metrics aligned with product and business goals; run controlled experiments (A/B tests, benchmarks) and communicate results clearly.

- Partner with software engineers, product managers, and business stakeholders to frame problems from both a scientific and business perspective.

- Investigate and fix production issues; ensure reliability, observability, and performance of AI systems.

- Stay actively engaged in technology watch on the latest AI trends (Generative AI, agentic systems, scalable ML, etc.).

Technical stack: Python, AWS, Airflow, Kubernetes, Gitlab, Snowflake, Vector databases (e.g. PGVector), LLM frameworks (OpenAI SDK, LangChain, LlamaIndex, or similar)

Profile Required

Must Have

- User-focused mindset with strong analytical skills and a result-oriented approach.

- 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: fine-tuning, prompt engineering, tool use, evaluation, and benchmarking.

- Experience with information retrieval and modern retrieval stacks: hybrid search, large-scale embeddings, vector databases, RAG architectures.

- Experience building or orchestrating agentic AI systems.

- Strong scientific rigor: ability to design metrics aligned with product goals, run controlled experiments, and communicate results to guide technical and product decisions.

- Experience with large-scale applications in production (monitoring, reliability, performance, observability).

- Strong coding skills in Python and proficiency in SQL.

- Proficient oral and written communication skills in English.

- Growth mindset: always striving to improve your technical and soft skills.

Nice to Have

- Experience in e-commerce or B2C marketplace environments.

- Familiarity with experimentation tools (W&B, MLFlow, Braintrust) and MLOps practices.

- Experience with scalable processing frameworks (Dask, Ray, Spark, etc.).

- Some familiarity with Bayesian inference and causal inference.

- Knowledge of recommendation systems and personalization.

What ManoMano Will Bring You

- 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

Recruitment Process

- Step 1: Introductory call with Justine Bourgeon, Talent Acquisition Manager

- Step 2: Manager interview with Thomas Sarazin

- Step 3: Take-home technical assignment

- Step 4: Technical interview

- Step 5: Final interview with Armelle Patault, VP Data


Apply now and join an exciting adventure ! ✨

You are welcome to apply to ManoMano, regardless of your gender, religion, age, sexual orientation, ethnicity, disability.