Azure AI/ML Engineer

Apptad Inc; Bellevue (WA); On-site; USD 120,000 - 160,000; Full time

Job summary

Apptad Inc. is seeking an ML Engineer to design, build, deploy, and maintain end-to-end ML solutions across data ingestion, model training, and production deployment systems.

The role requires developing data pipelines and implementing ML models with Python, and integrating models into APIs/services. Familiarity with Azure ML and enterprise security standards is preferred, with a focus on MLOps/CI/CD pipelines for automated training and deployment.

Qualifications

• Proven experience in designing, building, deploying and maintaining end-to-end ML solutions across data ingestion, model training and production deployment.
• Experience developing data pipelines and implementing ML models using Python.
• Knowledge of Azure services and Azure ML for enterprise-scale deployments.
• Understanding of enterprise security standards in ML infrastructure (Microsoft SFI knowledge helpful).
• Experience building MLOps/CI/CD pipelines for automated model training, validation and deployment.

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.

Skills

Python

Data pipelines

ML model deployment

Tools

Azure

Azure ML

Core .NET Technologies

OpenAI

DevOps

Job description

Must Have Technical/Functional Skills

Azure; Core .NET Technologies; Azure ML

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

Open AI; DevOps