Back
Metro location, mid-level (3–6 yrs), and a popular DevOps/MLOps title increase applicant competition.
Core infra skills transfer broadly, but MLOps/Vertex AI requirements add moderate domain specificity.
Explicit 3–6 year requirement plus mandatory Kubernetes, CI/CD, cloud, and MLOps tool experience raises strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own and manage scalable, secure, and cost-efficient cloud infrastructure supporting Virallens AI platforms across AWS, GCP, and potentially Azure.
Build and maintain CI/CD pipelines and automate Kubernetes deployments, including cluster management with horizontal and vertical scaling.
Implement monitoring, cost optimization, security, compliance, and governance frameworks to ensure high availability and performance of production AI/ML workloads.
3 to 6 years of experience in Infrastructure, DevOps, or MLOps roles supporting production AI/ML systems.
Strong hands-on expertise with Kubernetes and cloud infrastructure (AWS, GCP essential; Azure is a plus).
Proficiency with CI/CD tools such as Jenkins and Argo CD, and experience in container management (Docker, Docker Compose).
Experience managing distributed systems like Kafka and Redis, with a strong security and compliance focus.
Experience working in startup or fast-paced environments with high ownership and operational responsibility for AI/ML infrastructure.
Skilled in end-to-end infrastructure lifecycle for Generative AI or similar production ML systems, including scaling, monitoring, and cost optimization.
Comfortable collaborating closely with AI and engineering teams to directly impact product deliverables and grow toward senior infrastructure leadership roles.