Job descriptionJob 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