Developer- MLOPS

Required Qualifications :

• 6+ years of experience in machine learning operations or software / platform development.
• Strong experience with Azure ML, Azure DevOps, Blob Storage, and containerized model deployments on Azure.
• Strong knowledge of programming languages commonly used in AI / ML, such as Python, R, or C++.
• Experience with Azure cloud platform, machine learning services, and best practices. Roles :
• Design, develop, and maintain complex, high-performance, and scalable MLOps systems that interact with AI models and systems.
• Cooperate with cross-functional teams, including data scientists, AI researchers, and AI / ML engineers, to understand requirements, define project scope, and ensure alignment with business goals
• Offer technical leadership and expertise in choosing, evaluating, and implementing software technologies, tools, and frameworks in a cloud-native (Azure + AML) environment.
• Troubleshoot and resolve intricate software problems, ensuring optimal performance and reliability when interfacing with AI / ML systems.
• Participate in software development project planning and estimation, ensuring efficient resource allocation and timely solution delivery.
• Contribute to the development of continuous integration and continuous deployment (CI / CD) pipelines.
• Contribute to the development of high-performance data pipelines, storage systems, and data processing solutions.
• Drive integration of GenAI models (e.g., LLMs, foundation models) in production workflows, including prompt orchestration and evaluation pipelines.
• Support edge deployment use cases via model optimization, conversion (e.g., to ONNX, TFLite), and containerization for edge runtimes.
• Contribute to the creation and maintenance of technical documentation, including design specifications, API documentation, data models, data flow diagrams, and user manuals.

Preferred Qualifications :

Interested Candidates can also share the resumes on shraddha@careerstone.in

Note : - Candidates with maximum 1 month Notice period are preferred.