ML Ops Engineer

• Design and architect advanced auto CV/ML pipeline infrastructure
• Deliver a higher level of usability and reliability to end-user groups
• Support cloud-based MLOps at scale
• Work on Continuous Integration/Delivery for the internal user groups CV/ML projects
• Enhance and extend the DataOps and MLOps infrastructure and functional processes
• Sustain the internal user groups to make adequate use of the CV/ML channels

Job Requirements:

• Bachelor s/Master s degree in Engineering, Computer Science (or equivalent experience)
• 4+ years of relevant industry experience in MLOps, DevOps, Site Reliability, and other related aspects
• Strong proficiency with Python
• Extensive skills with AWS infrastructure or other cloud providers
• Experience with Jenkins or other CI/CD tools
• Understand primary ML practice and production workflows
• Demonstrable skills using Kubeflow/Kubernetes to build large scale production pipelines
• Sound leadership skills with an ability to train and supervise other ML engineers/data scientists to make efficient/effective use of the pipelines
• Core competency with infrastructure as code tools such as Terraform and Cloudformation
• Proficiency with large scale data pipelines is helpful