Deskripsi Pekerjaan
Are you a skilled Azure AI Engineer looking to make a significant impact? CLaaS2SaaS is seeking a talented professional to design, build, and deploy cutting-edge, AI-powered applications on the Microsoft Azure platform. In this role, you will play a pivotal part in our digital transformation journey, translating complex business needs into scalable, cloud-native AI solutions.
As part of our dynamic team in Jakarta, you will work closely with data scientists, software developers, and product managers to integrate Azure Cognitive Services, Azure OpenAI, and custom machine learning models into robust production systems. If you are passionate about cloud technology, generative AI, and building intelligent software that solves real-world problems, we want to hear from you!
Tanggung Jawab
- Design, develop, and deploy production-grade AI and machine learning solutions using Azure Cognitive Services, Azure OpenAI, and Azure Machine Learning.
- Collaborate with cross-functional teams to integrate AI capabilities into existing enterprise software and cloud architectures.
- Build and optimize data pipelines and ETL processes to support AI model training and real-time inference.
- Implement MLOps best practices, including model versioning, continuous integration/continuous deployment (CI/CD), and automated monitoring.
- Ensure the security, scalability, and cost-efficiency of deployed AI models on the Azure cloud platform.
- Troubleshoot, debug, and optimize performance of AI APIs and underlying cloud infrastructure.
- Keep up-to-date with the latest advancements in Azure cloud technologies and Generative AI to drive innovation within the team.
Kualifikasi
- Bachelor’s degree in Computer Science, Information Technology, or a related technical field.
- Minimum of 3+ years of experience as an AI Engineer, Machine Learning Engineer, or Cloud Engineer with a heavy focus on AI.
- Hands-on experience with Microsoft Azure cloud services (Azure OpenAI, Cognitive Services, Azure Databricks, Azure Kubernetes Service).
- Strong proficiency in programming languages such as Python, C#, or Java.
- Solid understanding of Machine Learning (ML) concepts, Natural Language Processing (NLP), and Generative AI frameworks.
- Experience implementing MLOps pipelines and using CI/CD tools (e.g., Azure DevOps, GitHub Actions).
- Relevant certifications, such as Azure AI Engineer Associate (AI-102) or Azure Solutions Architect, are highly preferred.