AI-ML Engineer(5+ Years of Experience)

AI-ML Engineer

Timming – 11am-8:30 pm

Location – Remote (1–2 days/month at any client office – PAN India)

Exp – 5+ years

Budget - 70K per month

Occasional travel: 1–2 days/month to any nearby client office location-Noida, Gurgaon, Indore, Bangalore, Hyderabad, Pune, Chennai)

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:

•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.