MLops

Role & responsibilities

Preferred candidate profile

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.