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Application ends: November 9, 2029
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Job Overview

  • Date Posted
    November 11, 2022
  • Offered Salary
    $220.00 - $250.00 / week
  • Expiration date
    November 9, 2029
  • Experience
    5 Year
  • Industry
    Designer Graphics
  • Qualification
    Certificate
  • Career Level
    Officer

Job Description

We are seeking an experienced AI IaaS and PaaS Specialist to join our team. The successful candidate will be responsible for designing, implementing, and managing AI solutions on cloud infrastructure using Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) models.

### Responsibilities:

– Design and architect AI solutions on cloud platforms like AWS, Azure, or GCP using IaaS and PaaS services
– Provision and configure cloud infrastructure resources (virtual machines, storage, networking) for AI workloads
– Deploy and manage AI platforms and services like machine learning pipelines, model training, and inference
– Optimize cloud resource utilization and cost for AI workloads
– Implement security, monitoring, and governance best practices for AI cloud deployments
– Collaborate with data engineers, ML engineers, and DevOps teams for end-to-end AI solution delivery
– Stay up-to-date with the latest cloud AI services and industry trends

### Requirements:

– Bachelor’s or Master’s degree in Computer Science, Engineering or a related field
– 3+ years of experience in cloud computing, preferably with AI/ML workloads
– Hands-on experience with major cloud providers like AWS, Azure, or GCP
– Proficiency in cloud IaaS and PaaS services like EC2, EKS, SageMaker, AML, etc.
– Experience with containerization technologies like Docker and Kubernetes
– Knowledge of AI/ML frameworks like TensorFlow, PyTorch, scikit-learn
– Familiarity with DevOps practices like CI/CD, infrastructure as code
– Strong programming skills in Python, Java, or related languages
– Excellent problem-solving, analytical, and communication skills[1][4]

Expected Timeline: 4-6 weeks
Key Skills: Cloud computing, IaaS, PaaS, AI/ML platforms, containerization, DevOps