Graduate AI ML Engineer
Job Summary
We are seeking an AI/ML Engineer with 1–5 years of experience to develop production-grade AI agents, chatbots, and RAG systems. You will work on predictive analytics, bridging LLMs with structured retail data to provide actionable insights for our platform. The role involves managing the full lifecycle of ML models from prototype to deployment within a collaborative environment.
Responsibilities
- Build AI agents and chatbots for retail insights
- Develop RAG pipelines with LLMs and structured data
- Perform ML modeling for forecasting and anomaly detection
- Transition ML models from prototype to production
Required Skills
- Python & API development
- Machine Learning (Regression/Time-series)
- LLMs / RAG / Prompt Engineering
- Cloud infrastructure & Vector databases
Job Details
What You’ll Do:
- 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
Requirements:
- 1–3 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
Benefits:
- Competitive compensation package.
- Comprehensive health and benefits coverage.
- A predominantly in-person, collaborative work environment located in Santiago 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.
- Computer provided: Krunchbox provides a computer for your work.
- Informal dress code: No dress code is enforced.
- Remote work policy: Hybrid (partly from home and partly at the office in Santiago, Chile).