Azure AI/ML Engineer

Northern Base; Bellevue (WA); On-site; USD 120,000 - 180,000; Full time

Job summary

Northern Base in Bellevue, WA seeks an ML Engineer to design, build, deploy and maintain end-to-end ML solutions covering data ingestion, model training and production deployment. The role emphasizes Python-based pipelines, API integration, and secure infrastructure aligned with enterprise standards.

You will contribute to MLOps/CI/CD pipelines, with emphasis on secure connections and identity-based access, and collaborate on AI-driven copilots and intelligent agents within the team.

Qualifications

• Experience designing ML solutions end-to-end across data ingestion, model training, and production deployment.
• Strong Python-based data pipelines and ML model deployment.
• Familiarity with enterprise security standards and compliant infrastructure.

Responsibilities

• An ML Engineer designs, builds, deploys, and maintains end to end machine learning solutions across data ingestion, model training, and production deployment systems.
• Capable of developing data pipelines and implementing ML models using Python while also having a basic understanding of integrating models into existing application layers (APIs / services).
• Microsoft SFI knowledge and experience in creating secure ML infrastructure aligned with enterprise security standards.
• Capable of building and maintaining MLOps / CI CD pipelines for automated model training, validation, and deployment using secure connections and identity based access.
• Good to have AI engineering skills as team is building custom co pilots and intelligent agents.
• Generic Managerial Skills, If any

Skills

Azure

Core .NET Technologies

Azure ML

Open AI

DevOps

Job description

Job Description

Must Have Technical/Functional Skills

• Azure
• Core .NET Technologies
• Azure ML
• Open AI
• DevOps

Roles & Responsibilities

• An ML Engineer designs, builds, deploys, and maintains end to end machine learning solutions across data ingestion, model training, and production deployment systems.
• Capable of developing data pipelines and implementing ML models using Python while also having a basic understanding of integrating models into existing application layers (APIs / services).
• Microsoft SFI knowledge and experience in creating secure ML infrastructure aligned with enterprise security standards.
• Capable of building and maintaining MLOps / CI CD pipelines for automated model training, validation, and deployment using secure connections and identity based access.
• Good to have AI engineering skills as team is building custom co pilots and intelligent agents.
• Generic Managerial Skills, If any