Brooksource

Machine Learning Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer on a 12-month contract in Charlotte, NC, with a pay rate of $70.00 – $80.00/hour. Requires 3+ years of ML engineering experience, proficiency in AWS SageMaker, Terraform, and Python, and a Bachelor's degree or equivalent experience.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
640
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🗓️ - Date
January 13, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Charlotte, NC
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🧠 - Skills detailed
#AI (Artificial Intelligence) #Docker #Terraform #ML (Machine Learning) #Model Deployment #Python #AWS SageMaker #SageMaker #Computer Science #AWS (Amazon Web Services) #Data Science #Libraries #Pandas #Deployment #Cloud #Kubernetes #NumPy
Role description
Machine Learning Engineer 12-month Contract (possible extension) Hybrid: Charlotte, NC (3x/wk onsite) $70.00 – 80.00/hour (D.O.E.) 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 include (but are not limited to): • 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. Minimum requirements: • 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.