AI Developer

Join our R&D team as an AI Developer, where you'll build AI-powered internal tools and data-driven systems that enhance decision-making across the organization. You'll work with behavioral and operational data from over 30 million websites and develop AI/ML-driven platforms that process and analyze large-scale operational data. This role requires strong proficiency in Python, experience with data processing at scale, and a solid understanding of ML fundamentals.

• Construire des outils internes alimentés par l'IA et des systèmes basés sur les données utilisés dans toute l'organisation, y compris des plateformes d'analyse, l'automatisation des rapports et l'intelligence de flux de travail.
• Développer des plateformes pilotées par l'IA/ML qui traitent et analysent des données opérationnelles à grande échelle provenant de plus de 30 millions de sites.
• Concevoir et déployer des systèmes RAG, des fonctionnalités alimentées par des LLM et des flux de travail agentiques qui génèrent des informations exploitables pour les équipes internes.
• You have the curiosity and desire to learn and grow your skills. The AI landscape moves fast and you keep up because you genuinely enjoy it, not because someone tells you to
• You take pride in the quality and craftsmanship of your work - clean code, proper error handling, thoughtful architecture, not just something that works on the happy path
• You're excited about building internal tools and data systems that may not have a flashy frontend but have massive impact on how an organization operates
• You're a builder at heart. You don't just use AI tools - you understand how they work under the hood, and you think about how to make them useful for real people, not just technically impressive
• You think about the user and the decision first, not the pipeline and the model. When you see data, your first instinct is to ask what question it answers for the person who needs it
• You're a self-starter who can take a loosely defined problem, figure out the right approach, and ship a working solution without needing to be told what to do next
• You're an excellent communicator, fluent in both verbal and written English. You can explain complex technical decisions to non-technical stakeholders without dumbing it down
• You're a team player who is comfortable working alongside other developers and doesn't take critical feedback personally
• You're comfortable owning the full stack of an AI project - from data exploration and model selection to building the API, deploying the service, and making sure it actually works in production
• The ability to iterate and ship ideas quickly without sacrificing code quality
• Hands-on experience with LLM frameworks and tools: LangChain, LlamaIndex, or similar. You should be able to build a RAG pipeline from scratch
• Exceptional troubleshooting skills - when something breaks in production at scale, you can diagnose it
• Experience building and deploying APIs (FastAPI, Flask, or similar) that serve ML models in production
• Strong proficiency in Python, including production-grade practices - proper packaging, testing, type hints, async where appropriate
• Experience with data processing at scale - SQL, pandas, Spark, or similar
• Competent with version control through Git and GitHub. Clean commit history, proper branching, code review through PRs
• Personal computer with reliable internet access
• Ability to keep complex systems simple. Simplicity is a core value
• Previous remote work experience. You know how to manage your time, communicate proactively, and stay productive without supervision
• Experience with vector databases (Pinecone, ChromaDB, FAISS, Qdrant, or similar) and embedding models
• Familiarity with cloud infrastructure (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)
• Solid understanding of ML fundamentals - not just API calls, but how models work, when to fine-tune vs prompt engineer, how to evaluate properly
• 3+ years of professional experience building AI/ML systems in production environments (not just POCs or hackathon projects)
• Availability to participate in audio/video meetings and be available on Slack between the hours of 9 AM - 1 PM EST daily
• Experience building multi-agent systems using CrewAI, LangGraph, AutoGen, or similar frameworks
• Experience with model fine-tuning (PEFT, LoRA, QLoRA) and quantization techniques for cost optimization
• Familiarity with MLOps practices - model versioning, drift monitoring, experiment tracking (MLflow, Weights & Biases, etc)
• Experience with Databricks, AWS SageMaker, or similar ML platforms
• Familiarity with the WordPress ecosystem, PHP, or SaaS product development. Understanding the end user (small business owners, bloggers, ecommerce operators) is valuable context
• Experience building internal tools and data platforms that non-technical teams rely on daily
• Published research, open-source contributions, or technical writing that demonstrates depth of understanding
• Experience with MCP (Model Context Protocol), function calling, structured output, or similar LLM integration patterns