Machine Learning Ops Engineer

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.

• 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.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in MLOps, Dev Ops, 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.

• 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.