Requirements
Requires 3-7 years of experience in building production-grade, scalable AI systems. Must have expertise in supervised/unsupervised learning, deep learning, NLP, computer vision, or generative AI (e.g., LLMs). Strong ML system architecture skills, understanding of model serving, API development (FastAPI, Flask), and optimizing model performance are essential. Familiarity with Docker, Kubernetes, CI/CD pipelines, MLOps tools (MLflow/Kubeflow), and cloud deployment on AWS or Azure is required.
Description
ROLE PROFILE Designs and develops scalable machine learning models and AI-drivensolutions to address complex business challenges and enhance decision-making processesKey Responsibilities Work with large and complex data sets to solve challenging businessproblems Efficient training and deployment of standard ML, NN, and Agentic models. Develop, train, and optimize machine learning models using state-of-the-artalgorithms and frameworks Build production grade end-to-end ML pipelines, including data ingestion,transformation, model training, validation, and deployment Automate workflows for model training, testing, and deployment usingCI/CD pipelines and MLOps tools Collaborate with cross-functional teams to integrate models into applicationsand deliver end-to-end solutions Finetune SLMs/LLMs and build complex AI architecturesProfessional Experience/Qualifications (3-7) years of experience in building production grade, scalable AI systems. Expert in supervised/unsupervised learning, deep learning, NLP, computervision, or generative AI (e.g., LLMs). Strong ML system architecture skills Understanding of model serving, API development (FastAPI, Flask), andoptimizing model performance for real-time or batch inference. General Knowledge of Docker, Kubernetes, CI/CD pipelines, and tools likeMLflow/Kubeflow for model lifecycle management (MLOps) Comfortable with deploying models on AWS or Azure Minimum Educational qualifications: Bachelor's degree in Computer Science,Engineering, or related field requiredClassified: Internal FABInternal Preferred Education qualifications: Master or PhD in Computer Science or arelated field.