Artificial Intelligence Engineer

Job Title: AI/ML Engineer

Experience: 5+years

Location: Remote/ 1-2 day in a month

Timings: 11am to 8:30 pm

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

• Bachelor’s or master’s 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.