Back
Tier-1 brand, mid-level generalist title, and metro location drive high competition.
Core MLOps/devops skills are transferable across industries but expect domain-specific security and ML constraints.
Mandatory 3+ years, CKAD certification, specific tooling and security requirements make filtering strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Builds and maintains deployment pipelines, containers, and infrastructure-as-code for AI/ML production services.
Implements monitoring, logging, and alerting to ensure production AI/ML services' reliability and security.
Participates in on-call support, incident response, and contributes to technical design and code reviews with a focus on AI-assisted development tools.
3+ years of applied software engineering experience with formal training or certification.
Proficiency in Python and familiarity with modern software engineering practices.
Working knowledge of containerization (Docker) and Kubernetes with certification (e.g., CKAD).
Experience with CI/CD pipelines, cloud-native deployment, monitoring, and enterprise-authorized AI-assisted development tools.
Experienced in deploying and maintaining AI/ML production platforms with strong emphasis on reliability and security.
Practitioner of AI-assisted coding practices with ability to critically evaluate and validate AI-generated code.
Comfortable working in agile settings, participating in code reviews, incident management, and knowledgeable about responsible AI usage in workflows.