Bachelor’s or Master’s in Computer Science, Engineering, Mathematics, Statistics, or related field.
3-5 years of hands-on experience in AI / ML engineering and Python, with a demonstrable focus on building production ready models.
Solid understanding of machine learning algorithms, deep learning architectures, natural language processing (NLP), and information retrieval techniques (e.g., RAG)
Proven ability to deploy and manage AI / ML solutions on at least one major cloud platform.
Experience with MLOps principles and tools for model deployment, monitoring, and lifecycle management.
Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Containerization Docker and Kubernetes, OpenShift
Key Responsibilities :
Prepare, clean, and process large datasets; build and maintain data pipelines.
Develop and implement machine learning models for various applications (classification, regression, clustering, recommendations, etc.).
Engineer features and optimize model performance through hyper parameter tuning and validation.
Automating model building, training and deployment by building CI / CD / CT Pipelines
Stay updated on new tools and techniques in machine learning and AI.