AboutAbout LemrockTomorrow, in an agentic world, it won’t be humans browsing and buying on the web anymore, it will be AI agents acting on their behalf. A massive replatforming of the web is currently underway, and Lemrock is building the infrastructure to power that shift.We are a deeptech startup specializing in agentic commerce: we enable brands (Leroy Merlin, Lidl, Rakuten…) to sell their products directly within conversational agents like ChatGPT.We're taking the fundamentals from Criteo (models, performance, rapid iteration) and applying them to new AI interfaces. Jean-Baptiste Rudelle, co-founder of Criteo, is an investor and board member.We're the first to operate this channel at scale, with a proprietary stack and concrete results:100+ million conversational interactions analyzed monthly60+ brands onboardedMulti-million fundraising from top-tier investorsJob DescriptionContextYou'll join a tight-knit team with high product standards and direct access to production deployment: our models are tested in real-world conditions, with several million users each month, with very short cycles between prototyping, integration and deployment.In this context, you'll work on the next generation of agentic and recommendation systems — building the pipelines, agents, and models that sit at the core of our product.Your MissionYour goal is to build and scale the agentic infrastructure that powers Lemrock's commerce intelligence — turning raw signals into automated, self-improving systems at production scale.Concretely, You WillAnalyze large-scale conversational interaction datasets (100M+ events/month) to uncover behavioral patterns, intent signals, and performance drivers.Design and deploy agentic pipelines end-to-end — from data ingestion and enrichment to model orchestration, monitoring, and continuous improvement — integrated into systems exposed to millions of requests daily.Build autonomous agents that keep our knowledge infrastructure accurate and current.Translate insights into iteration loops in production, by updating, fine-tuning, and improving our existing recommendation and ranking algorithms with tight constraints on latency, robustness, and business outcomes.Design and train new recommendation models from scratch when needed, with a focus on scalability, evaluation rigor, and deployability in real-world traffic.Preferred ExperienceCandidate ProfileStrong academic background (MVA, ENS, X, Central…)2+ years of experience in AI, Agentic Systems, ML / Deep Learning, statistics or NLPExperience prototyping and deploying AI models into productionExperience with production systems (APIs, monitoring, optimization)Strong interest in LLMs, recommendation and conversational systems: building agentic pipelines, agent orchestration, fine-tuningComfortable with AI coding tools (Claude Code, Cursor)Thrives in ambiguity and 0-to-1 environmentsFluent in English; French is a plusTech StackML/AI (required)Agentic frameworks (e.g., Langchain) and/or native SDKs like OpenAI/AnthropicObservability and evaluation for LLM/agent workflows (e.g., LangSmith)Vector search, scoring, prompting, LLM orchestrationHybrid recommender systems, causal inference, probabilistic modelsBonus (appreciated But Not Required)TypeScriptEngineering: Docker, GCP, PostgreSQL, Redis, Vector DBs, PostHogCI/CDRecruitment ProcessWhy Join UsJoin a company in early breakout mode, already generating revenue, with a clear technological edge and strong financial backing to fuel its growthWork directly with an experienced team: two repeat YC founders who’ve scaled product & tech before, a former strategy/innovation director (10 years in the sector), and ex-strategy consultants (McKinsey QuantumBlack, BCG)Be part of the next structural shift of the web — agentic interfacesOwn mission-critical topics, grow fast, and shape the company’s future trajectoryAdditional InformationContract Type: Full-TimeLocation: Paris Education Level: Master's DegreeExperience: > 2 yearsOccasional remote authorized