DevOps Engineer – MLOps & AI Platform

About the role

Join Dailoqa as a DevOps Engineer responsible for operationalizing cutting‑edge machine learning and generative AI solutions. You will collaborate with data scientists, ML engineers, and business stakeholders to build robust MLOps pipelines that enable rapid experimentation and reliable production deployment of AI models.

Key responsibilities

• Design and implement scalable, cost‑optimized, and secure infrastructure for AI‑driven platforms.
• Implement infrastructure‑as‑code using Terraform, ARM templates, or CloudFormation.
• Automate provisioning, CI/CD pipelines, and model deployment workflows.
• Ensure version control, repeatability, and compliance across all infrastructure components.
• Set up monitoring, logging, and alerting with Prometheus, Grafana, ELK, or Azure Monitor.
• Optimize performance and resource utilization of GPU‑based training and inference workloads.
• Work with Snowflake and Databricks for collaborative ML development and scalable data processing.
• Contribute to open‑source MLOps tools and communities.
• Maintain awareness of model interpretability, responsible AI, governance, and regulatory compliance.
• Explore LangChain, vector databases (FAISS, Pinecone) and retrieval‑augmented generation pipelines.

Required profile

• Proven experience with one or more major cloud platforms (AWS, Azure, GCP).
• Strong background in containerization and orchestration (Docker, Kubernetes, Helm).
• Hands‑on experience with CI/CD tools such as GitHub Actions, Jenkins, Azure DevOps, or ArgoCD.
• Proficiency in scripting languages (Python, Bash, PowerShell).
• Familiarity with MLOps frameworks (MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML).
• Understanding of DevOps principles applied to machine‑learning workflows.
• Excellent communication and cross‑functional collaboration skills.

Required skills

• AWS
• Azure
• GCP
• Terraform
• ARM templates
• CloudFormation
• Docker
• Kubernetes
• Helm
• GitHub Actions
• Jenkins
• Azure DevOps
• ArgoCD
• Python
• Bash
• PowerShell
• MLflow
• Kubeflow
• SageMaker
• Vertex AI
• Azure ML
• Prometheus
• Grafana
• ELK
• Azure Monitor
• Snowflake
• Databricks
• LangChain
• FAISS
• Pinecone