AI Applied Scientist

We are looking for a highly skilled and passionate AI Applied Scientist to join our growing AI/ML team. The ideal candidate should have strong expertise in Data Science, Machine Learning, and MLOps, with hands-on experience in deploying machine learning models into production environments. This role requires a strong problem-solving mindset, deep technical knowledge, and the ability to work on scalable AI solutions that drive real business impact.

Responsibilities:

• Design, develop, and deploy scalable Machine Learning and AI models for real-world business problems.
• Build end-to-end ML pipelines including data preprocessing, feature engineering, model training, validation, deployment, and monitoring.
• Work closely with engineering and product teams to integrate ML solutions into production systems.
• Develop and maintain MLOps workflows for continuous integration, deployment, monitoring, and retraining of models.
• Optimise model performance, scalability, and reliability in production environments.
• Conduct experimentation, model evaluation, and performance analysis using statistical and machine learning techniques.
• Collaborate with cross-functional stakeholders to understand business requirements and translate them into AI-driven solutions.
• Stay updated with the latest advancements in AI, Machine Learning, Generative AI, and MLOps technologies.

Requirements:

• M. Tech / MS in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, or related fields.
• 3-6 years of hands-on experience in Data Science / Machine Learning roles.
• Strong programming skills in Python.
• Solid understanding of Machine Learning algorithms, statistical modelling, and predictive analytics.
• Hands-on experience with ML frameworks and libraries such as Scikit-learn, TensorFlow, PyTorch, XGBoost, etc.
• Strong experience in deploying ML models into production environments.
• Good understanding of MLOps concepts and tools.
• Experience with Docker, Kubernetes, MLflow, Airflow, CI/CD pipelines, or similar technologies.
• Experience working with cloud platforms such as AWS, Azure, or GCP.
• Strong knowledge of SQL and data processing techniques.
• Excellent problem-solving and analytical skills.

Preferred Qualifications:

• Experience in building scalable AI/ML systems in production.
• Exposure to model monitoring, retraining, and optimisation.
• Knowledge of Generative AI / LLM-based applications is a plus.
• Experience in the BFSI, fintech, or risk analytics domain will be an added advantage.

Skills

Airflow, ML, MLOps, MLflow, Python, Machine Learning