Mlops cloud azure Aws with Kubernetes and fast API

Job description Job Summary: We are looking for a skilled MLOps Engineer who specializes in deploying and managing machine learning models using cloud-native CI/CD pipelines , FastAPI , and Kubernetes , without Docker . The ideal candidate should be well-versed in scalable model serving, API development, and infrastructure automation on the cloud using native container alternatives or pre-built images. Key Responsibilities: Design, develop, and maintain CI/CD pipelines for ML model training, testing, and deployment on cloud platforms (Azure/AWS/GCP) . Develop REST APIs using FastAPI for model inference and data services. Deploy and orchestrate microservices and ML workloads on Kubernetes clusters (EKS, AKS, GKE, or on-prem K8s). Implement model monitoring, logging, and version control without Docker-based containers. Utilize alternatives such as Singularity, Buildah, or cloud-native container orchestration . Automate deployment pipelines using tools like GitHub Actions, GitLab CI, Jenkins, Azure DevOps , etc. Manage secrets, configurations, and infrastructure using Kubernetes secrets, ConfigMaps, Helm, or Kustomize . Work closely with Data Scientists and Backend Engineers to integrate ML models with APIs and UIs. Optimize performance, scalability, and reliability of ML services in production. Required Skills: Strong experience with Kubernetes (deployment, scaling, Helm/Kustomize) . Deep understanding of CI/CD tools like Jenkins, GitHub Actions, GitLab CI/CD, or Azure DevOps. Experience with FastAPI for high-performance ML/REST APIs. Proficient in cloud platforms (AWS, GCP, or Azure) for ML pipeline orchestration. Experience with non-Docker containerization or deployment tools (e.g., Singularity , Podman , or OCI-compliant methods ). Strong Python skills and familiarity with ML libraries and model serialization (e.g., Pickle, ONNX, TorchServe). Good understanding of DevOps principles, GitOps, and IaC (Terraform or similar) . Preferred Qualifications: Experience with Kubeflow, MLflow , or similar tools. Familiarity with model monitoring tools like Prometheus, Grafana, or Seldon Core . Understanding of security and compliance in production ML systems. Bachelor's or Master’s degree in Computer Science, Engineering, or related field. Industry Technology, Information and Internet Employment Type Full-time Job Types: Full-time, Permanent Pay: ₹35,000.00 - ₹50,000.00 per month Work Location: In person