MLOps Engineer / AI ML Engineer (Specialist - Data Sciences)

LTM

$110K — $130K *
Tampa, FL 33647In-Person
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in MLOps within the Blueverse ML Engineering domain.
  • Strong background in designing and maintaining MLOps pipelines.
  • Proficiency in automation for CI/CD of ML models.
  • Experience with infrastructure optimization for ML training and deployment.
  • Familiarity with security governance and quality standards in ML operations.
  • Capability to analyze performance and troubleshoot ML deployment issues.
  • Knowledge of current trends and best practices in MLOps.

Responsibilities

  • Lead the implementation of MLOps frameworks for machine learning.
  • Collaborate with data science teams for production-ready solutions.
  • Develop automated workflows for model versioning and deployment.
  • Monitor deployed models for performance and initiate retraining as needed.
  • Mentor junior engineers on MLOps tools and best practices.
  • Drive initiatives for improving ML operational efficiency.
  • Coordinate with DevOps to manage ML environments.

Benefits

  • Opportunity to work in a cutting-edge environment focused on MLOps.
  • Mentorship opportunities for career development.
  • Participation in cross-functional teams for diverse project exposure.
  • Engagement in continuous improvement initiatives.
  • Access to the latest tools and technologies in ML engineering.
Full Job Description
Role description

Title: MLOps Engineer

Location: Tampa, FL

Seeking a candidate with a 5 to 7 years of experience in MLOps within the Blue verse ML Engineering domain to drive scalable and efficient machine learning operations

Job Description
• Design develop and maintain robust MLOps pipelines to streamline model deployment and monitoring Collaborate with data scientists and engineers to operationalize machine learning models ensuring scalability and reliability Implement automation for continuous integration and continuous delivery CICD of ML models Optimize infrastructure and workflows for effective model training deployment and lifecycle management Ensure compliance with security governance and quality standards in ML operations Analyze system performance and troubleshoot issues related to ML model deployment and monitoring Stay updated with the latest trends and best practices in MLOps and machine learning engineering Participate in cross functional teams to integrate ML solutions into production environments

Roles and Responsibilities
• Lead the end-to-end implementation of MLOps frameworks within the Blueverse ML Engineering family Collaborate closely with data science teams to translate experimental models into production ready solutions Develop and maintain automated workflows for model versioning testing deployment and rollback Monitor deployed models for performance degradation and initiate retraining or tuning as necessary Mentor junior engineers and share knowledge on MLOps best practices and tools Drive continuous improvement initiatives to enhance ML operational efficiency and scalability Coordinate with infrastructure and DevOps teams to provision and manage ML environments Document processes architectures and operational procedures to ensure knowledge sharing and compliance

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