Job Overview

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We are a dynamic team focused on building scalable and secure machine learning solutions in cloud environments. Our projects involve designing and deploying end-to-end MLOps pipelines, containerized workloads, and automated CI/CD processes using Azure services. We leverage cutting‑edge technologies such as Azure ML, Kubernetes, Docker, MLflow, and Terraform to deliver robust, production‑ready AI solutions.

Key Technologies

• Azure Machine Learning
• Azure Kubernetes Service (AKS)
• Azure DevOps
• Docker
• Kubernetes
• MLflow
• Terraform
• Python
• CI/CD
• IaC

Qualifications

• Proficiency in Python; 3+ years of experience in developing ML pipelines and integrating with frameworks (PyTorch, TensorFlow).
• Hands‑on experience with Azure services including Azure ML, AKS, and Azure DevOps for end‑to‑end MLOps workflows.
• Strong knowledge of containerization and orchestration using Docker and Kubernetes for scalable, fault‑tolerant deployments.
• Familiarity with MLOps practices including MLflow for experiment tracking, model registry, and artifact management.
• Experience with infrastructure as code (IaC) using Terraform, Bicep, or ARM templates for automated and secure cloud environments.

Nice to Have

• Experience with Kubeflow or Vertex AI for advanced ML orchestration.
• Background in Python‑based ML frameworks (PyTorch, Scikit‑learn, TensorFlow).
• Knowledge of data privacy, compliance, and responsible AI principles.

Soft Skills

• Analytical Thinking – Ability to interpret data, identify trends, and provide actionable insights to drive business decisions.
• Problem‑Solving – Proactively identify and resolve issues related to BI systems, ensuring smooth operations and data accuracy.
• Effective Communication – Ability to explain technical concepts to non‑technical stakeholders clearly and concisely, fostering understanding and collaboration.
• Attention to Detail – Meticulous in data validation, report generation, and ensuring data quality across BI platforms.
• Team Collaboration – Strong interpersonal skills to work effectively in cross‑functional teams, coordinating with IT, business analysts, and other stakeholders.
• Adaptability and Continuous Learning – Open to learning new tools and technologies in the rapidly evolving BI landscape and adjusting to changing business needs.

Responsibilities

• Design and implement end‑to‑end MLOps pipelines in Azure using services like Azure ML, AKS, ACR, and Azure Data Lake.
• Containerize and orchestrate machine learning workloads using Docker and Kubernetes for scalable, fault‑tolerant deployment.
• Automate training, validation, and deployment of models through CI/CD pipelines integrated with Git and workflow orchestration tools (Airflow, MLflow, Kubeflow).
• Manage model versioning, lineage, and registry using Azure ML Model Registry or equivalent.
• Implement monitoring and alerting for model drift, data quality, and inference performance.
• Ensure infrastructure as code (IaC) using tools like Terraform, Bicep, or ARM templates.
• Apply security and compliance best practices across model storage, API endpoints, and data access.

Benefits

• Your Journey With Us Starts Here
• Initial Screening: If you meet our requirements, our recruiter will reach out to you for a chat about your motivations and expectations.
• Technical Interview: Next, youll be invited to showcase your skills in an interview with one of our technical experts or team members.
• Final Interview: Finally, youll have the opportunity to meet your future Team Lead.

Seniority Level

Mid‑Senior level

Employment Type

Full‑time

Job Function

Engineering and Information Technology

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