Deskripsi Pekerjaan
Join the cutting-edge team at Nanyang Technological University to architect scalable AI infrastructure. We are seeking a dedicated Platforms Engineer, MLOps to build the robust foundation for Singapore's future in Artificial Intelligence. In this pivotal role, you will design, deploy, and maintain advanced machine learning pipelines that empower researchers and data scientists to focus on innovation rather than infrastructure management. Your contributions will directly support national AI initiatives, ensuring high performance, security, and accessibility across our platforms. You will be responsible for bridging the gap between machine learning research and production deployment, creating a seamless environment that accelerates scientific discovery and drives national technological advancement.
Tanggung Jawab
- Design and implement scalable MLOps infrastructure and tools to support national AI efforts.
- Build and maintain CI/CD pipelines for training, validating, and deploying machine learning models.
- Collaborate closely with data scientists and researchers to optimize model training workflows and reduce time-to-market.
- Implement cloud-native solutions on AWS, GCP, or Azure, ensuring cost-efficiency and scalability.
- Establish monitoring, logging, and alerting systems to guarantee high availability and reliability of AI services.
- Automate deployment processes and infrastructure provisioning to streamline development cycles.
- Enforce security best practices and data governance policies for AI workloads.
Kualifikasi
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field.
- 3+ years of professional experience in MLOps, Platform Engineering, or DevOps, preferably within the academic or research sector.
- Strong proficiency in Python, SQL, and scripting languages.
- Deep experience with containerization technologies (Docker, Kubernetes) and orchestration.
- Hands-on experience with cloud platforms (AWS, GCP, or Azure) and serverless architectures.
- Familiarity with ML frameworks (TensorFlow, PyTorch) and model versioning tools (MLflow, DVC).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.