AI ML Engineer LLM Chatbots, RAG , Predictive Modeling)
- Build AI agents (“Krunchy”) that generate Insights, Reports, Recommendations
- Develop RAG pipelines combining LLMs with structured data (POS, inventory, product data)
- Create chat-based experiences for customer analytics
- Machine Learning Modeling (Core): build and improve models for Demand forecasting, Stockout risk, Lost sales estimation, Anomaly detection
- Perform feature engineering on messy retail datasets
- Model evaluation and iteration
- Help take models from prototype → production
- Tech Stack: Python (FastAPI preferred), LLM APIs (OpenAI, Anthropic), LangChain / LlamaIndex (or similar), Vector databases, ClickHouse / modern data stack, AWS / cloud infrastructure
2–4 years of experience in ML, data science, or backend engineering
Strong Python skills
Experience building APIs or backend systems
Experience with machine learning modeling (e.g., regression, time-series, classification, or similar)
Exposure to LLMs, chatbots, or prompt engineering
Comfortable working with messy datasets
Nice to Have: RAG or vector search experience; Time-series forecasting (Prophet, XGBoost, etc.); Retail / supply chain data experience; MLOps or production ML exposure
Why Join: Build real AI products (not just models); Work on LLMs, chatbots, and predictive ML systems; High ownership and fast growth; Be part of a major platform rebuild
Compensation: Competitive salary; Health benefits; Hybrid work model
Optional (but high leverage): Please include examples of ML models or LLM projects you’ve built (GitHub or portfolio).
- Competitive compensation package.
- Comprehensive health and benefits coverage.
- A predominantly in-person, collaborative work environment located in Santiago De Chile, to encourage fast iteration and real-time problem solving.
- Opportunity to scale and lead a global SaaS platform that solves real-world customer challenges.
- A direct, impactful role in shaping the future of AI-powered supplier-retailer collaboration.