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 field

- 5+ years of hands-on experience in machine learning engineering or AI/ML development using Python and cloud-based tools

- Deep expertise in large language models (LLMs) such as GPT, Gemini, and related architectures

- 1+ years of experience working with Generative AI and Retrieval-Augmented Generation (RAG) systems in production environments

- Proficient in designing and deploying LLM-powered applications using LangChain, LangGraph, and vector databases like FAISS and Pinecone

- Strong understanding of deep learning architectures (e.g., Transformers) with practical experience using ML frameworks such as PyTorch, TensorFlow, Keras, and Scikit-learn

- Proficiency in data manipulation and analysis using Pandas, NumPy, and other Python data libraries

- Hands-on experience with Microsoft Azure, including Azure Machine Learning, Azure DevOps, and other cloud-native services for scalable ML workflows

- Familiarity with REST APIs, containerization (Docker), and CI/CD pipelines

- Excellent analytical, problem-solving, and communication skills, with the ability to collaborate effectively across cross-functional teams

- Azure 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.