Position Details
About this role
This role involves managing the full lifecycle of machine learning models, automating deployment pipelines, and ensuring system reliability and compliance across cloud environments.
Key Responsibilities
- Manage model lifecycle
- Implement real-time monitoring
- Develop automated CI/CD pipelines
- Provision scalable infrastructure
- Enforce model governance standards
Technical Overview
The technical environment includes cloud platforms (AWS, GCP, Azure), Kubernetes, Terraform, and monitoring tools, focusing on scalable AI system operations.
Ideal Candidate
The ideal candidate is a mid-level ML engineer with 3+ years experience in MLOps, cloud infrastructure, and model lifecycle management. They should have strong skills in automation, monitoring, and cloud platforms like AWS, GCP, or Azure.
Must-Have Skills
Nice-to-Have Skills
Tools & Platforms
Required Skills
Hard Skills
Soft Skills
Industry & Role
Keywords for Your Resume
Deal Breakers
Less than 3 years experience in MLOps, No experience with cloud platforms (AWS, GCP, Azure), Lack of knowledge in model monitoring or governance, No experience with Kubernetes or Terraform
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