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

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

Job description Company Description Dataviv Technologies is a cutting-edge Artificial Intelligence research company that is pioneering the world's first accessible and applied Ai lab, transforming AI education across schools, colleges, and universities, as well as research across top labs globally. Role Description This is a full-time on-site role for a Mlops Kubernetes Engineer at Dataviv Technologies located in Gurugram. The Mlops Kubernetes Engineer will be responsible for maintaining, developing, and optimizing Kubernetes clusters, implementing MLOps processes, and ensuring smooth deployment and scaling of AI models in production environments. Qualifications Proficiency in Kubernetes, Docker, and container orchestration Experience with MLOps processes and tools Strong understanding of cloud technologies, such as AWS or GCP Knowledge of CI/CD pipelines and automation tools Experience with monitoring and logging tools like Prometheus and Grafana Bachelor's or Master's degree in Computer Science or related field Excellent problem-solving and analytical skills Strong communication and collaboration abilities Industry Technology, Information and Internet Employment Type Full-time Edit job description Job Types: Full-time, Permanent Pay: ₹30,000.00 - ₹40,000.00 per month Work Location: In person Speak with the employer +91 9867786230