AI / ML Fellowship Program

Job Description Position Title : AI / ML Fellowship Associate Program Duration : 6 – 8 Months (Full-Time Fellowship) Role Summary The AI / ML Fellowship Associate will participate in a structured, project-based learning program designed to build foundational and intermediate skills in artificial intelligence, machine learning, and data science. Fellows will work on real-world AI / ML projects, receive mentorship from industry experts, and collaborate with technical and business teams to gain practical experience across the complete machine learning lifecycle — problem framing, data engineering, model development, model evaluation, deployment, and monitoring. Throughout the fellowship, associates will apply statistical methods, machine learning algorithms, and AI frameworks to build innovative, production-ready models that solve real business and societal problems. Key Responsibilities • Project Execution & Documentation • Complete assigned AI / ML projects such as exploratory data analysis, feature engineering, model building, and hyperparameter tuning. • Build supervised and unsupervised machine learning models tailored to project requirements (e.g., regression, classification, clustering, recommendation systems). • Use Python libraries and ML frameworks such as NumPy, Pandas, Scikit-learn, TensorFlow, and PyTorch to implement models. • Document datasets used, feature engineering choices, model performance, and deployment workflows. • Research & Framework Development • Research AI / ML best practices, MLOps methodologies, and current state-of-the-art algorithms. • Propose enhancements to models, feature engineering approaches, and ML workflows to improve performance and scalability. • Contribute to the creation of reusable model templates, experimentation logs, and evaluation frameworks. • AI / ML Deployment & Model Monitoring • Deploy machine learning models using APIs, cloud services, or containerized environments. • Support model monitoring and performance tracking to detect drift, fairness issues, or anomalies. • Integrate automation workflows and CI / CD principles into ML deployments using MLOps toolchains. • Stakeholder Collaboration • Work closely with mentors, technical team members, and domain experts to understand problem statements and validate outcomes. • Participate in peer code reviews, ML research discussions, project showcases, and technical presentations. • Incorporate feedback to improve model interpretability, decision transparency, and business relevance. Learning Outcomes • Develop proficiency in the end-to-end AI / ML lifecycle : data preparation, model development, performance evaluation, deployment, and monitoring. • Gain hands-on experience with supervised / unsupervised learning, deep learning fundamentals, and applied MLOps workflows. • Strengthen scientific research thinking, experiment design, model optimization, and technical communication skills. • Build a portfolio showcasing ML models, analytics case studies, deployment pipelines, and AI-driven solutions — demonstrating job readiness for AI / ML roles. Qualifications • Graduate degree in AI, ML, Data Science, Computer Science, Statistics, Engineering, Mathematics, or related fields. • Recent graduates or early-career professionals with a strong passion for AI / ML preferred. • Proficiency in Python and familiarity with ML libraries (Scikit-learn, TensorFlow, PyTorch) required; SQL and data visualization tools are an advantage. • Strong analytical thinking, mathematical reasoning, and curiosity for research. • Clear written and verbal communication skills. Program Benefits • Structured mentorship from AI / ML professionals, regular feedback sessions, and personalized career development coaching. • Opportunities to present ML research and projects to industry experts and receive professional evaluations. • Fellowship certificate and digital badge upon successful completion. • Accelerated pathway to roles such as Machine Learning Engineer, Data Scientist, AI Research Associate, MLOps Engineer, or Applied AI Engineer. 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