Job Specifications
Location: Paris, Châtelet – Hybrid (2 days on-site / 3 days remote)
Contract: Full-time (CDI)
Team: Technology – Direct report to CTO
Main Mission
Identify, design, and deploy AI and Machine Learning solutions that concretely increase the value delivered by the Mendo application to our users. As a Senior Data Scientist / AI Engineer, you will be the technical pioneer of AI integration into our product, with full autonomy to explore, experiment, and implement ML and GenAI models (fine-tuning, embeddings, RAG, etc.). Your mission: transform business opportunities into pragmatic and measurable AI solutions integrated in Mendo, serving over 60 enterprise clients (PwC Global, BDO, EY...). You will mentor a junior Data Scientist and establish the standards of excellence for data science practice at Mendo.
Key Responsibilities
Proactive AI Opportunity Identification
Be constantly on the lookout: analyze the product, usage patterns, and customer feedback to identify where AI can create concrete value.
Propose relevant AI use cases aligned with product roadmap and business objectives.
Ruthlessly challenge and prioritize AI initiatives: absolute focus on user impact and ROI.
Collaborate closely with the Product Lead and PMs to transform business needs into actionable AI opportunities.
Establish a framework for prioritizing AI projects based on impact, feasibility, and effort.
Model Research, Development, and Deployment
Research and experiment with ML and GenAI models (LLMs, embeddings, classification, clustering, recommendation).
Fine-tune existing models (OpenAI, Anthropic, open-source) rather than building from scratch.
Design and implement end-to-end AI pipelines: data prep, training/fine-tuning, evaluation, deployment.
Develop RAG (Retrieval-Augmented Generation), semantic search, and other relevant GenAI architecture solutions.
Optimize model performance and costs in production (latency, tokens, infrastructure).
Implement monitoring and continuous quality evaluation systems for models.
Ruthless Pragmatism and Efficiency
Prioritize ruthlessly: know when to say no to "cool" AI projects without real impact.
Favor simple and effective solutions: avoid over-engineering and POCs that lead nowhere.
Iterate quickly: prototype fast, test with real users, measure impact, and pivot if necessary.
Maintain constant balance between exploration (R&D) and execution (value delivery).
Document technical decisions and trade-offs clearly and concisely.
Technical Leadership and Mentoring
Mentor and train a junior Data Scientist: share your expertise, define growth objectives, and delegate effectively.
Establish data science and AI engineering best practices at Mendo (code quality, MLOps, experimentation).
Collaborate closely with development squads to integrate models into the product.
Evangelize AI possibilities internally and educate product and business teams.
Progressively build the data science practice at Mendo in preparation for team growth.
Cross-functional Collaboration
Work hand-in-hand with the CTO to align AI strategy with overall technical vision.
Collaborate with product teams to understand user pain points and imagine AI solutions.
Coordinate with development teams to ensure smooth integration of models into production.
Interact with Customer Success teams to understand real usage and measure AI feature impact.
Regularly present your results and recommendations to stakeholders (product, sales, leadership).
Required Skills
Knowledge & Technical Expertise
Machine Learning expertise: minimum 4-6 years of experience in ML model development and deployment.
Deep mastery of LLM fine-tuning (OpenAI, Anthropic, Llama, Mistral, etc.).
Solid experience with GenAI architectures: RAG, embeddings, semantic search, advanced prompt engineering.
Knowledge of ML/DL frameworks: PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex.
Experience with cloud platforms for ML (Azure ML, AWS SageMaker, or Google Vertex AI).
Python mastery and data science libraries (scikit-learn, pandas, numpy, etc.).
Knowledge of vector databases (Pinecone, Weaviate, Qdrant, etc.).
Familiarity with MLOps pipelines: model versioning, A/B testing, production monitoring.
Understanding of cost, latency, and scalability challenges for AI solutions in production.
Know-how
Ruthless pragmatism: demonstrated ability to prioritize effectively and deliver value quickly.
Opportunity identification: track record of AI use case proposals that created measurable business impact.
End-to-end ownership: experience from research through deployment and production monitoring.
Ability to prototype rapidly and iterate based on user feedback.
Excellence in model evaluation and benchmarking (metrics, rigorous experimentation).
Clear communication of complex technical concepts to non-technical audiences.
Experience in close collaboration with product and engineering teams.
Ability to mentor and train more junior profiles.
Soft Skills
Product mindset: ob
About the Company
At Mendo, we start from a simple truth: technology evolves fast, but teams aren’t always equipped to keep up. Our mission? Empower every employee to work effectively with AI, by focusing on what really matters: their job, their tools, their day-to-day work. Mendo integrates directly into the workflow and reinforces the right habits at the right time for lasting adoption. Our solution combines technology, seamless integration, and memory anchoring, built for large enterprises seeking to onboard every employee into the AI jour...
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