Graduate AI ML Engineer
Job Summary
We are looking for an AI/ML Engineer to help build production-grade chatbots, RAG systems, and predictive models. The role involves building AI agents, developing RAG pipelines for retail data, and performing feature engineering. You will be responsible for taking models from prototype to production within a modern retail analytics platform.
Responsibilities
- Build AI agents for insights and reporting
- Develop RAG pipelines for structured data
- Create chat-based analytics experiences
- Perform ML modeling and feature engineering
- Take models from prototype to production
Required Skills
- Python & Backend/API development
- LLMs, RAG, and Vector databases
- Machine Learning & Time-series forecasting
- Retail data handling
- MLOps experience
Job Details
Responsibilities:
- 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.
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.
- RAG or vector search experience.
- Time-series forecasting (Prophet, XGBoost, etc.).
- Retail / supply chain data experience.
- MLOps or production ML exposure.
Tech Stack:
- Python (FastAPI preferred).
- LLM APIs (OpenAI, Anthropic).
- LangChain / LlamaIndex (or similar).
- Vector databases.
- ClickHouse / modern data stack.
- AWS / cloud infrastructure.