MLOps Engineer with Azure Experience

Utilize Azure technologies like Azure Cognitive Technologies, Azure Machine Learning, and Azure Bot Services to design, create, and deploy AI/ML based applications.

Include AI components into data workflows, engage with data scientists and data engineers.

Utilize Azure AI services to implement natural language processing (NLP) create and implement machine learning models and algorithms.

Automate the deployment and monitoring of AI models, collaborate with DevOps teams.

Use AI to automate processes such as sentiment analysis, image identification, recommendation systems, and chatbots.

Implementing machine learning pipelines and workflows

Deploying and scaling ML models in production environments

Automating CI/CD pipelines to account for data, code, and model changes

Monitoring model performance and applying updates as needed

Ensuring the security and compliance of machine learning systems

Collaborating with data scientists to optimize models and improve performance

Bachelor’s Degree, (BA/BS) in Information Systems from a four-year college or university and 5 or more years of development experience required or equivalent combination or education and experience

Total of 3-6 years of experience in managing machine learning projects end-to-end, with the last 18 months focused on MLOps

Strong programming skills, preferably in languages like Python, Java, or Scala

Proficiency in machine learning libraries and frameworks, such as TensorFlow, PyTorch, or scikit-learn

Experience with containerization technologies, like Docker and Kubernetes

Familiarity with ML model deployment tools, such as MLflow or Kubeflow

Working experience in Azure cloud platform