Deploy and manage Kubernetes clusters and Docker containers for ML workloads

Build and maintain automation using Jenkins, Argo Workflows, Argo Events, and Argo CD

Write Bash and Python scripts to automate infrastructure and ML pipelines

Work across cloud platforms (AWS, Azure, GCP) to configure and manage cloud-native components like: Kubernetes (AKs, EKS, GKE) Storage (e.g., S3, Blob, GCS) Compute (e.g., EC2, Azure VMs, GCE) Networking (e.g., VPC, Load Balancers) IAM and Secrets Management

Monitor and troubleshoot infrastructure for ML pipelines

Collaborate with the MLOps lead to explore and integrate new tools and practices

Bash scripting

Docker & Kubernetes

Jenkins or similar CI/CD tools (e.g:Github actions)

Python scripting

One or more cloud platforms (AWS, Azure, GCP)

Basic networking concepts

Interest or experience in the Argo ecosystem (Workflows, Events, CD)

Exposure to MLOps tools like MLflow, Airflow etc

Experience deploying ML models or pipelines in cloud/on-premise air gapped environments

Degree in Computer Science, Machine Learning, or related field.

Exceptional analytical and problem-solving skills.

Fast learner with a proactive mindset and eagerness to grow

Clear communicator and effective collaborator

Submit your application

If the above does not work, you may email us your CV (pdf format) at jobs@betterdata.ai