Demo

Machine Learning Engineer

TRIMAH TECHNOLOGIES LLC
Columbus, OH Full Time
POSTED ON 3/19/2025
AVAILABLE BEFORE 4/15/2025

Job Summary

As an MLOps Engineer, you will be responsible for the end-to-end productionization and deployment of machine learning models at scale. You will collaborate closely with data scientists to refine models and ensure they are optimized for production. Additionally, you will maintain and improve our MLOps infrastructure, automate deployment pipelines, and ensure compliance with IT and security standards. Your role will be critical in image management, vulnerability remediation, and the deployment of ML models using modern infrastructure-as-code practices.

Key Responsibilities

  • Oversee the end-to-end productionization and deployment of machine learning models.
  • Collaborate with data scientists to refine and optimize models for production.
  • Maintain and enhance MLOps infrastructure.
  • Automate deployment pipelines.
  • Ensure compliance with IT and security standards.
  • Manage image management and vulnerability remediation.
  • Deploy ML models using infrastructure-as-code practices.

API Experience

  • Develop and maintain APIs and data pipelines for seamless integration of machine learning model outputs into our Kafka-based event hub platform.
  • Strong background in Python, API development (batch and real-time), Kafka, FTP / SFTP automation, and Linux operating systems.
  • Work closely with data scientists to understand and finalize the schema of model outputs.
  • Document schemas using Swagger.
  • Collaborate with event hub architects to ensure accurate and reliable data publication through Kafka APIs, automated FTP processes, or custom-developed APIs for real-time integration.
  • Qualifications

  • Proven experience in MLOps, machine learning model deployment, and infrastructure management.
  • Proficiency in Python, API development, Kafka, FTP / SFTP automation, and Linux.
  • Strong understanding of IT and security standards.
  • Excellent collaboration and communication skills.
  • Experience with infrastructure-as-code practices.
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