Azure ML Engineer / Machine Learning Engineer

Purple Drive LLC; Washington (District of Columbia); Sur place; USD 120 000 - 180 000; Plein temps

Résumé du poste

Purple Drive LLC is seeking an ML Engineer in Washington, D.C. to design, build, deploy, and maintain end-to-end ML solutions spanning data ingestion, model training, and production deployment systems.

The role focuses on developing data pipelines and implementing ML models in Python, while integrating models into APIs/services. Familiarity with secure ML infrastructure and MLOps/CI-CD pipelines is required; experience with AI engineering for co-pilots and intelligent agents is a plus.

Qualifications

• Experience designing end-to-end ML solutions across data ingestion, model training, and deployment.
• Proficiency in Python for data pipelines and model implementation.
• Understanding of integrating ML models into APIs/services within applications.
• Knowledge of secure ML infrastructure compliant with enterprise security standards.

Responsabilités

• Design, build, deploy, and maintain end-to-end ML solutions across data ingestion, training, and production systems.
• Develop data pipelines and implement ML models using Python; integrate models with APIs/services.
• Create secure ML infrastructure aligned with enterprise security standards (Microsoft SFI knowledge advantageous).
• Build and maintain MLOps/CI-CD pipelines for automated training, validation, and deployment with secure connections and identity-based access.
• Contribute AI engineering skills for co-pilots and intelligent agents as part of product development.

Connaissances

Azure

Azure ML

Core .NET Technologies

Description du poste

Role DescriptionMust 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.