- 経験
- どれでも
- 給料
- —
- 求人情報
- 1
- 投稿済み
- 6時間前
- Work mode
- 在任中
- Resume
- Required to apply
Where you'll work
仕事内容
Role overview
This position is for an AI Engineer who can build, deploy, and refine intelligent solutions using Microsoft Azure AI services. The work centers on Azure-native machine learning and data capabilities to create systems that are scalable, reliable, and ready for production use.
What you'll do
- Create and implement AI-driven solutions with Azure AI tools and services.
- Train, deploy, and manage machine learning and AI models in the Azure cloud.
- Develop APIs and service layers that connect AI features with enterprise applications.
- Handle both structured and unstructured datasets for model development and inference.
- Partner with business and technical stakeholders to shape AI requirements.
- Release, observe, and fine-tune AI solutions within Azure environments.
- Maintain strong performance, scalability, and dependability across AI systems.
- Investigate issues and improve existing AI implementations when needed.
Required background
- Practical, hands-on exposure to Microsoft Azure AI and Azure Machine Learning.
- Solid understanding of AI/ML fundamentals and the full model lifecycle.
- Experience exposing and using models through APIs.
- Strong coding ability in Python, Java, or comparable languages.
- Working knowledge of data pipelines and data processing workflows.
- Familiarity with REST API integration and system architecture concepts.
Preferred experience
- Experience with Azure App Service, Functions, AKS, and Data Factory.
- Exposure to machine learning libraries such as Scikit-learn, TensorFlow, or PyTorch.
- Understanding of MLOps and CI/CD practices for ML deployment.
- Experience using cloud monitoring and logging platforms.
- Ability to evaluate model quality and improve performance through tuning.
Soft skills
- Strong analytical thinking and problem-solving ability.
- Clear communication and effective teamwork.
- Comfort working in Agile delivery environments.
- Interest in learning and adapting to evolving cloud AI technologies.