Posted:1 week ago| Platform:
On-site
Full Time
About QpiAI is a deep tech startup pioneering next-generation computing platforms, empowering enterprises to innovate and deploy AI solutions seamlessly across cloud and edge devices at scale. We're dedicated to making it easier to build meaningful AI powered experiences. Key Responsibilities Take ownership of infrastructure layer for on-premise and cloud deployments. Assist development teams in designing scalable and portable applications. Establish best practices within the organisation and help developers ship fast without breaking things. Product ownership and manage periodic reporting to management and senior leadership. Mentor team members to adopt a platform-first mindset. Ideal Profile Experience in DevOps engineering with Docker, Kubernetes, and shell scripting. Experience with distributed GPU systems and ML infrastructure. Expertise with cloud platforms like AWS, Azure, and GCP. Experience building robust infrastructure for training and serving machine learning models. Ability to set up multi-node Kubernetes clusters and use managed Kubernetes services. Nice to Have Experience with ML orchestration services like kubeflow, flyte, prefect. Knowledge on MLOps concepts like model and data versioning. Experience with distributed computing frameworks like ray. Skills: Docker,Kubernetes,shell scripting,distributed GPU systems,ML infrastructure,Data Annotation,Data Curation,Model Registry,Model Serving,Workflow Orchestration,Retrieval Augmented Generation (RAG),Agentic Workflows,CUDA_ERROR_VERSION_MISMATCH,multi node kubernetes clusters,managed kubernetes services,kube native tooling,Ansible,Terraform,pulumi,scalable data lakes,data processing pipelines,highly available services,databases,AWS,Azure,GCP,networking principles,load balancing,DNS configurations,proxies,integration and deployment pipelines,ML orchestration services,kubeflow,flyte,prefect,distributed computing frameworks,ray,Role-Based Access Control (RBAC) principles,MLOps concepts,model and data versioning,orchestration,model serving,modern distributed applications Show more Show less
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