Primary Responsibilities

• Develop and deploy AI/ML models, with a focus on both generative and traditional approaches.
• Build, fine-tune, and integrate Large Language Models (LLMs) and generative AI applications, enhancing capabilities like context understanding, data synthesis, and recommendation generation.
• Create and maintain data pipelines and workflows to support prompt engineering and model training.
• Implement, optimize, and scale ML pipelines using cloud services such as Azure (Azure AI Foundry, Azure ML, Cosmos DB) or AWS (Sagemaker, Lambda, EC2, Bedrock).
• Collaborate with cross-functional teams to translate business requirements into AI solutions.
• Ensure models are scalable, reliable, and secure in production environments.
• Continuously monitor model performance, retrain, and update models to improve results.

Required Skills

• Proficiency in Python and machine learning frameworks (TensorFlow, PyTorch, Scikit-learn).
• Hands-on experience with Azure or AWS cloud platforms, including services like AI Foundry, Bedrock, Lambda, EC2, and Sagemaker.
• Strong understanding of machine learning techniques (e.g., NLP, CV, regression, clustering).
• Experience in API development and integrating NLP/LLM models into applications.
• Familiarity with MLOps tools and practices (CI/CD, model monitoring, versioning).

Posted By