MLOps Engineer - Cloud Infrastructure

ML Ops Engineer (Remote).

Are you passionate about scaling machine learning models in the cloud? Were on the hunt for an experienced ML Ops Engineer to help us build scalable, automated, and production-ready ML infrastructure across multi-cloud environments.

Location : Remote.

Experience : 5+ Years.

What Youll Do :

- Own the full ML lifecycle: training versioning deployment monitoring.

- Build cloud-native infrastructure on AWS, GCP, or Azure.

- Automate deployment using CI/CD tools like Jenkins, GitLab.

- Containerize and orchestrate ML apps with Docker and Kubernetes.

- Use tools like MLflow, TensorFlow Serving, Kubeflow.

- Partner with Data Scientists & DevOps to ship robust ML solutions.

- Set up monitoring systems for model drift and performance issues.

What Were Looking For :

- Hands-on with at least two cloud platforms : AWS, GCP, or Azure.

- Proficient in Python and ML libraries (TensorFlow, Scikit-learn, etc.)

- Strong skills in Docker, Kubernetes, and cloud infrastructure automation (Terraform/CloudFormation).

- Experience building CI/CD pipelines (Jenkins, GitLab CI/CD, etc.

- Familiarity with tools like MLflow, TensorFlow Serving.

Must have skills :