Unknown Company

Machine Learning Ops Engineer

town of texas, wi • Posted 1 weeks ago
Onsite Full Time Electrical & Energy Engineering

We are seeking a Machine Learning Operations (MLOps) Engineer to support the development and maintenance of infrastructure and tools for deploying and monitoring machine learning models.

This role is part of a team that delivers modern cloud-based data solutions to support Sales, Marketing, Finance, and AI/ML analytics capabilities.

The ideal candidate will collaborate closely with data scientists and engineers to ensure scalable, secure, and efficient model operations.

Key Responsibilities

  • Model Deployment and Management: Develop and manage scalable and reliable deployment processes for machine learning models in production environments.
  • Infrastructure Automation: Design and implement automated workflows for model training, testing, and deployment using tools such as Jenkins, Docker, and Kubernetes.
  • Aerospike Management: Utilize Aerospike for high-performance data storage and retrieval to support ML applications.
  • API Development: Build and maintain robust APIs for integrating models with various applications and services.
  • Collaboration: Work closely with cross-functional teams to translate business requirements into technical solutions.
  • Monitoring and Optimization: Implement monitoring tools to track model performance and system health, and optimize infrastructure as needed.
  • Security and Compliance: Ensure all deployed models and systems adhere to industry standards and security protocols.

Required Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
  • 3+ years of experience in MLOps, DevOps, or a related field with a focus on machine learning.
  • 1+ years of experience developing solutions on AWS cloud platform.
  • Proficiency in Python and/or Java with strong coding and debugging skills.
  • Experience with CI/CD practices and tools.
  • Proven experience with container-based systems such as Docker.

Preferred Qualifications

  • Experience with Kubernetes and cloud-native architecture.
  • Familiarity with Aerospike or similar high-performance data stores.
  • Exposure to agile development environments and cross-functional collaboration.

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