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About
A leading utility provider in Charlotte is seeking an experienced Machine Learning Engineer to join the team that builds, deploys, and maintains ML models internally. In this role, you will support ML model deployment and engineering of new ML/AI features to be used across the organization. If you are seeking a collaborative space to utilize and hone your MLOps skills, keep reading and apply! Responsibilities
Support deployments, validation, and optimization of ML models utilized by data scientists across the organization using Terraform and AWS SageMaker. Monitor model performance and implement automated retraining processes, optimizing performance and cost efficiency. Debug and troubleshoot issues in deployment pipelines and production, using Terraform and Concourse. Engineer new features and solutions, deploy these, and support the platform for model development and deployment. Qualifications
A completed Bachelor's degree in Computer Science or related field; or 8 years of equivalent work experience. 3+ years of experience in machine learning engineering, or related, roles, ideally deploying ML models and tuning these for performance. Extensive experience using AWS cloud services, specifically SageMaker + Terraform, for deploying and supporting ML models. Strong proficiency writing Python scripts and utilizing ML libraries (PANDAS, NumPy, etc.) to enhance, build, or deploy ML models. Deep understanding of MLOps practices and tools (Docker, Kubernetes, CI/CD). What's in it for you?
Join a collaborative innovative team at the forefront of modern ML model usage at a major utility provider where you will be owning cutting-edge ML initiatives. Utilize your expertise in enterprise ML to support an entire enterprise through your ML model deployments. Learn how data operates and flows in an enterprise utility and use your expertise to guide others along the ML journey. Enroll in weekly paychecks and comprehensive health benefits. #J-18808-Ljbffr
Languages
- English
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