AI/ML Intern

About the Role Fairdeal.market runs B2B quick-commerce operations through dark-store warehouses across Delhi NCR. Its AI/ML systems are directly involved in logistics, computer vision, and agentic tooling used in live operations. The AI team is deliberately lean, giving interns the opportunity to own end-to-end problems — from framing the problem and building models to evaluating results and deploying solutions to production. The role is suited for someone who thinks in systems rather than just notebooks and is comfortable moving from an initial hypothesis to a monitored and versioned production service. What You'll Work On • Build and deploy machine learning solutions for real-world operational problems • Work with machine learning, deep learning, LLMs, generative AI, and RAG systems • Design multi-agent and tool-using workflows • Build integrations with APIs, databases, and production services • Develop and evaluate models using modern ML frameworks and tools • Design evaluation systems for both traditional ML and LLM/RAG applications • Build testing, monitoring, retraining, and deployment workflows • Work with production ML infrastructure, observability, and MLOps practices • Contribute to computer vision and other AI-driven applications where required

• 0–1 years of experience • Strong Python skills and a solid understanding of machine learning fundamentals, including bias and variance, regularization, evaluation design, and appropriate use of ML • Practical experience with pandas, NumPy, scikit-learn, and at least one deep-learning framework such as PyTorch or TensorFlow • Familiarity with LLMs and generative AI, including RAG architectures, prompt engineering, and grounding techniques • Experience with data processing, feature pipelines, preprocessing, and querying using MongoDB or SQL • Understanding of multi-agent and tool-using workflows, including planning, state management, and controlled tool invocation • Familiarity with orchestration frameworks such as LangGraph or LangChain • Experience integrating agents with APIs, databases, and services using MCP or equivalent integration layers • Experience building and iterating on models using scikit-learn, XGBoost, LightGBM, PyTorch, or Hugging Face Transformers • Knowledge of feature engineering, hyperparameter optimization, and experiment tracking using tools such as MLflow or Weights & Biases • Familiarity with LLM fine-tuning and prompt or RAG optimization • Ability to design evaluation frameworks for ML and LLM/RAG systems • Experience with unit and regression testing for ML code using tools such as pytest • Understanding of data and model drift monitoring and retraining workflows • Familiarity with serving models using FastAPI, Docker, and AWS services such as Bedrock, SageMaker, or Lambda/ECS • Familiarity with CI/CD, GitHub Actions, model registries, and dataset/model versioning • Understanding of production observability, including logging, latency monitoring, quality monitoring, and safe rollouts • Pursuing or recently completed a degree in Computer Science, IT, Data Science, or a related field • Self-directed and comfortable researching documentation, debugging independently, and solving problems without constant supervision • Ability to objectively evaluate and report results based on data