Description

You will design, build, and deploy AI/ML solutions and MLOps pipelines on Azure, ensuring models are production-ready, scalable, and monitored.

This role is remote.

Responsibilities

• Build and maintain end-to-end ML pipelines for training, testing, deployment, and monitoring using Azure Machine Learning.
• Implement CI/CD pipelines to support continuous integration and delivery of data, code, and models.
• Productionize models developed by data scientists, ensuring scalability, performance, and reliability.
• Automate model deployment, monitoring, and lifecycle management processes.
• Integrate AI capabilities into enterprise data workflows, including NLP, computer vision, and recommendation systems.

Required Skills

• 8+ years of experience in software/data engineering or machine learning.
• Strong programming skills in Python, Java, or Scala.
• Hands-on experience with Azure cloud services, especially Azure Machine Learning.
• Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Proficiency in containerization and orchestration tools (Docker, Kubernetes).
• Familiarity with MLOps tools such as MLflow, Kubeflow, or similar.
• Bachelor’s degree in Computer Science, Information Systems, or related field (or equivalent experience).
• Proven track record of building and deploying ML models into production environments.

Preferred Skills

• Recent hands-on MLOps experience.
• Experience collaborating cross-functionally with Data Engineering, Data Science, and DevOps teams.

Key Skills

Education

Bachelor's degree