Applied AI Researcher

Overview

We are seeking an AI Researcher to join our R&D team to develop practical AI and machine learning solutions for real-world analytical problems. This role focuses on predictive modelling, statistical analysis, LLM-powered AI agents, and intelligent systems operating across structured and unstructured data.

Responsibilities

• Develop and evaluate predictive models including regression, classification, and forecasting models.
• Conduct EDA, statistical experimentation, hypothesis testing, and model validation on large datasets.
• Build and experiment with LLM systems involving RAG, AI agents, fine-tuning, LoRA, and vector databases.
• Develop scalable Python-based AI/ML pipelines and reproducible workflows.
• Work with structured and unstructured datasets, including text, image, audio, and multimodal data.

Requirements

• Proven experience training or fine-tuning machine learning and/or LLM models on datasets with at least 1 million records.
• Hands-on experience with one or more LLM fine-tuning techniques such as LoRA, QLoRA, PEFT, or SFT.
• Strong background in predictive analytics, statistical modelling, and machine learning.
• Experience evaluating model performance using experimentation, metrics, validation frameworks, and failure analysis.
• Experience working with large-scale structured and unstructured datasets.
• Strong Python programming skills with Pandas, NumPy, Scikit-learn, SciPy, Matplotlib, and SQL.
• Experience building reproducible AI/ML pipelines and workflows.
• Good understanding of supervised, unsupervised, and generative AI models.

Preferred

• Experience with RAG, AI agents, LangChain/LangGraph, vector databases, or multimodal AI systems.
• Bachelor's, Master's, or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative discipline.