AI ML Engineer
Location : Remote (WFO once in a month)
Multiple Location
Must Have :
Python, AIML Modules, Gen AI Model, Azure Cloud, LLM, And AI models.
Primary Responsibilities :
- Design, develop, and deploy AI / ML models using Python, Azure Machine Learning and GenAI model.
- Integrate AI solutions with Microsoft Cloud services such as Azure Functions, Azure Data Lake, Azure Synapse, and Azure Cognitive Services.
- Collaborate with data scientists, software engineers, and business stakeholders to understand requirements and deliver scalable solutions.
- Optimize and monitor model performance in production environments.
- Ensure security, compliance, and best practices in cloud-based AI deployments.
- Stay current with emerging AI technologies and trends, especially within the Microsoft ecosystem
Job Description :
Bachelors or masters degree in computer science, Machine Learning, Artificial Intelligence, Data Science, Engineering, Mathematics, Statistics, or a related field5+ years of hands-on experience in machine learning engineering or AI / ML development using Python and cloud-based toolsDeep expertise in large language models (LLMs) such as GPT, Gemini, and related architectures1+ years of experience working with Generative AI and Retrieval-Augmented Generation (RAG) systems in production environmentsProficient in designing and deploying LLM-powered applications using LangChain, LangGraph, and vector databases like FAISS and PineconeStrong understanding of deep learning architectures (e.g., Transformers) with practical experience using ML frameworks such as PyTorch, TensorFlow, Keras, and Scikit-learnProficiency in data manipulation and analysis using Pandas, NumPy, and other Python data librariesHands-on experience with Microsoft Azure, including Azure Machine Learning, Azure DevOps, and other cloud-native services for scalable ML workflowsFamiliarity with REST APIs, containerization (Docker), and CI / CD pipelinesExcellent analytical, problem-solving, and communication skills, with the ability to collaborate effectively across cross-functional teamsAzure certifications (e.g., Azure AI Engineer Associate, Azure Data Scientist Associate).Experience with MLOps and model lifecycle management.Familiarity with healthcare data standards (X12, HL7) is a plus.Experience with Power BI or other Microsoft analytics tools.(ref : hirist.tech)