AI/MLOps Engineer (with DevOps)

·        Operate and manage Kubernetes or
OpenShift clusters for multi-node orchestration

·        Deploy and manage LLMs and other AI
models for inference using Triton Inference Server or custom endpoints

·        Automate CI/CD pipelines for model
packaging, serving, retraining, and rollback using GitLab CI or ArgoCD

·        Set up model and infrastructure
monitoring systems (Prometheus, Grafana, NVIDIA DCGM)

·        Implement model drift detection,
performance alerting, and inference logging

·        Manage model checkpoints, reproducibility
controls, and rollback strategies

·        Track deployed model versions using
MLFlow or equivalent registry tools

·        Implement secure access controls for
model endpoints and data artifacts

·        Collaborate with AI / Data Engineer to
integrate and deploy fine-tuned datasets

·        Ensure high availability, performance,
and observability of all AI services in production

Requirements

·        3+ years experience in DevOps, MLOps, or
AI/ML infrastructure roles

·        10+ overall experience with solution
operations

·        Proven experience with Kubernetes or
OpenShift in production environments, preferably certified.

·        Familiarity with deploying and scaling
PyTorch or TensorFlow models for inference

·        Experience with CI/CD automation tools with
Open Shift / Kubernetes

·        Hands-on experience with model registry
systems (e.g., MLFlow, KubeFlow)

·        Experience with monitoring tools (e.g.,
Prometheus, Grafana) and GPU workload optimization

·        Strong scripting skills (Python, Bash)
and Linux system administration knowledge