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AI and Machine Learning Specialist

2 miesięcy temu

Wrocław, Polska Engenious Pełny etat
Develop AI and ML Models for Microsoft Azure

At Engenious, we are seeking a skilled AI and Machine Learning Specialist to join our team. This role involves developing, deploying, and managing AI and ML models within a Microsoft Azure-based infrastructure. As an AI and ML Specialist, you will be responsible for end-to-end model workflows, including data preprocessing, model deployment, monitoring, and CI/CD automation.

Key Responsibilities:
  • Develop and deploy AI and ML models using frameworks like TensorFlow, PyTorch, and Scikit-learn.
  • Set up and maintain workflows on Azure Machine Learning (AML) for model training, deployment, and lifecycle management.
  • Prepare, process, and engineer features on large datasets, leveraging platforms such as Databricks.
  • Design and implement CI/CD pipelines for AI and ML models using Azure DevOps, applying MLOps best practices.
  • Configure and manage containerized environments with Docker, Kubernetes, and Azure Kubernetes Service (AKS) for model deployment and scaling.
  • Automate model testing and build scripts using Python.
  • Monitor and log model performance metrics with Azure Monitor and Application Insights to ensure stability and optimize model performance.
  • Collaborate effectively with cross-functional teams to communicate model insights and performance metrics.

Skills and Experience:
  • Proficiency in AI/ML frameworks – experience with TensorFlow, PyTorch, and Scikit-learn for model development.
  • Hands-on experience with Azure Machine Learning (AML) – ability to manage ML model training, deployment, and performance tracking on AML.
  • Data engineering skills – expertise in data preparation, transformation, and feature engineering, ideally using Databricks.
  • CI/CD expertise – experience designing and maintaining CI/CD pipelines for AI/ML models using Azure DevOps.
  • Familiarity with containerization and orchestration tools – practical knowledge of Docker, Kubernetes, and AKS.
  • Strong Python skills – proficiency in automation and scripting for model deployment and testing.
  • Experience in monitoring and logging – skilled in using Azure Monitor, Application Insights, and logging metrics for model optimization.
  • Statistical modeling skills – capability to apply statistical methods and communicate insights effectively with teams.