Description

Key Responsibilities

Design, develop, and deploy AI/ML solutions using Azure services (e.g., Azure Machine Learning, Cognitive Services)

Build and maintain end-to-end machine learning pipelines for training, testing, deployment, and monitoring

Productionize models developed by data scientists, ensuring scalability, performance, and reliability

Implement CI/CD pipelines to support continuous integration and delivery of data, code, and models

Automate model deployment, monitoring, and lifecycle management processes

Monitor model performance and retrain/update models as needed

Integrate AI capabilities into enterprise data workflows and applications

Develop solutions leveraging NLP, computer vision, recommendation systems, and chatbot technologies

Collaborate cross-functionally with Data Engineering, Data Science, and DevOps teams

Ensure security, governance, and compliance of ML systems and data pipelines

Required Qualifications

Bachelor’s degree in Computer Science, Information Systems, or related field (or equivalent experience)

3–6 years of experience in software/data engineering or machine learning, including recent hands-on MLOps experience

Strong programming skills in Python (preferred), Java, or Scala

Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn

Hands-on experience with Azure cloud services, especially Azure Machine Learning

Experience with containerization and orchestration tools (Docker, Kubernetes)

Familiarity with MLOps tools such as MLflow, Kubeflow, or similar

Experience building and deploying ML models into production environments

Key Skills

Education

Bachelor's degree