Data Scientist - Artificial Intelligence

We are seeking a passionate Data Scientist - Artificial Intelligence to develop and deploy AI/ML solutions that solve complex business and engineering challenges. The ideal candidate should have a strong foundation in Machine Learning, Deep Learning, Generative AI, data analysis, and Python programming, with the ability to work across the complete AI lifecycle from data preparation to model deployment.

Responsibilities:

• Develop, train, evaluate, and deploy Machine Learning and Deep Learning models.
• Build AI-powered solutions using Generative AI, Large Language Models (LLMs), and NLP techniques.
• Perform data collection, cleansing, feature engineering, and exploratory data analysis.
• Design and implement predictive, classification, recommendation, and optimisation models.
• Work with structured and unstructured datasets to extract actionable insights.
• Develop APIs and services to integrate AI models into enterprise applications.
• Collaborate with software engineers, data engineers, and business stakeholders to deliver AI solutions.
• Monitor model performance and support model retraining and optimisation.
• Document experiments, model results, and technical approaches.

Requirements:

• Strong programming skills in Python.
• Good understanding of Machine Learning, Statistics, and Data Science fundamentals.
• Experience with TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy, or similar frameworks.
• Knowledge of Generative AI, LLMs, Prompt Engineering, RAG, LangChain, or related technologies.
• Experience with SQL and data manipulation techniques.
• Understanding of REST APIs and cloud-based AI services.
• Familiarity with Linux environments and software development best practices.
• Strong analytical, problem-solving, and communication skills.

Preferred Skills:

• Exposure to MLOps, Docker, Kubernetes, and model deployment workflows.
• Knowledge of cloud platforms such as Azure, AWS, or GCP.
• Experience with vector databases, AI agents, and modern AI frameworks.
• Certified Kubernetes Administrator (CKA) certification is an added advantage.
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Statistics, Mathematics, or related field.

Skills

Deep Learning, ML, Machine Learning, PyTorch, Python, Scikit-learn, TensorFlow