AI Infrastructure Specialist

7 hours ago

Singapore beBeeinfrastructure Full time $90,000 - $130,000
Job Title: AI Infrastructure Specialist

About the Role:
This is an exciting opportunity for a highly skilled AI Engineer to join our team as an AI Infrastructure Specialist. As a key member of our infrastructure team, you will be responsible for designing, building, and maintaining scalable and efficient AI/ML platforms. Your expertise in cloud computing, containerization, and data engineering will enable us to deliver cutting-edge AI solutions to our customers.

Key Responsibilities:
  • Design and implement reliable, scalable, and secure AI/ML infrastructure on cloud platforms (e.g., Azure).
  • Collaborate with data scientists to set up and maintain development and production environments for AI/ML workloads.
  • Develop robust data ingestion and transformation pipelines to support AI/ML model training and inference at scale.
  • Work closely with cross-functional teams to integrate AI solutions with existing systems through APIs, microservices, or other integration methods.

Main Requirements:
Proficiency in Python programming and Linux systems.

Strong background in software engineering, data engineering, or AI infrastructure. Hands-on experience with cloud platforms (e.g., Azure) and containerization tools (Docker, Kubernetes). Familiarity with building RESTful APIs and/or lightweight front-end tools for AI interfaces. Solid understanding of MLOps practices and tools (e.g., MLflow, FastAPI). Excellent communication skills to collaborate across technical and business teams. Growth mindset with the drive to learn and master new technologies.

Nice to Have:
Exposure to big data processing and streaming tools (e.g., Kafka, Spark).

Knowledge of AI/ML frameworks such as TensorFlow or PyTorch. Experience with CI/CD pipelines and infrastructure-as-code tools (e.g., Terraform, Jenkins). Familiarity with security, monitoring, and performance tuning of AI services.

Tell Employers What Skills You Have:
Python Programming, Containerization, Scalability, Performance Tuning, Data Engineering, Software Engineering, Microservices, FastAPI, Docker, Big Data, Pipelines, TensorFlow, PyTorch, Cloud Computing, Azure, Kubernetes, Security, Monitoring, MLOps

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