AI & ML

Role Overview

We are seeking an ML/ AI Research Analyst who bridges rigorous mathematical theory with production-grade engineering in one of the leading institutions of the precision-obsessed diamond industry. In this role, you will design, develop, and debug complex mathematical models from first principles, moving beyond simple API calls to deep architectural implementation.

Responsibilities

• Mathematical Formulation & Modelling: Translate vague, complex business problems into clean mathematical frameworks, cost functions, and optimization problems.
• Architecture & Implementation: Build, train, and fine-tune classical machine learning models and deep neural networks from the ground up using Python and core ML libraries.
• Algorithm Debugging & Optimization: Diagnose performance bottlenecks including vanishing/exploding gradients, data leakage, and overfitting by evaluating model behaviours at the mathematical and tensor levels.
• Production Deployment: Write modular, well-tested, and optimized Python code to deploy models into production environments with low latency and high reliability.
• Hands-On Prompt Engineering & LLM Systems: Craft, test, and systemize advanced prompt strategies and integrate them into production LLM orchestration pipelines.

Requirements

• Mathematical Logic & Deep Learning Fundamentals: Deep, intuitive grasp of linear algebra, multivariable calculus, probability theory, optimization algorithms (SGD, Adam, L-BFGS), and statistical inference.
• Neural Network Internals: Clear conceptual understanding of backpropagation mechanics, attention mechanisms, normalization layers, and loss function formulation.
• Python Mastery: Advanced proficiency in Python (beyond Pandas/NumPy/SciPy/Scikit-Learn) with strong software engineering practices like modular design and vectorized operations.
• Prompt Engineering & LLM Integration: Demonstrated experience in prompt optimization, guardrailing, and managing context window constraints (Bonus Skill).

Skills

• Python
• PyTorch
• TensorFlow
• Scikit-Learn
• LLMs

Benefits

• Food provided
• Health insurance