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Job Title: Senior Machine Learning Engineer
Location: Charlotte, NC
Experience: 10 Years
Employment Type: Long-term contract
Job Summary
We are looking for a highly skilled Senior Machine Learning Engineer with strong expertise in AWS SageMaker, Terraform, MLflow, PySpark, and Python. The selected candidate will design, deploy, and optimize end-to-end machine learning pipelines while ensuring automation, scalability, and performance in a distributed environment. This position requires deep technical proficiency in MLOps and cloud infrastructure management on AWS.
Key Responsibilities
Job Title: Senior Machine Learning Engineer
Location: Charlotte, NC
Experience: 10 Years
Employment Type: Long-term contract
Job Summary
We are looking for a highly skilled Senior Machine Learning Engineer with strong expertise in AWS SageMaker, Terraform, MLflow, PySpark, and Python. The selected candidate will design, deploy, and optimize end-to-end machine learning pipelines while ensuring automation, scalability, and performance in a distributed environment. This position requires deep technical proficiency in MLOps and cloud infrastructure management on AWS.
Key Responsibilities
- Design and implement scalable ML models and pipelines using AWS SageMaker and PySpark.
- Develop infrastructure as code solutions using Terraform for ML environments.
- Manage and optimize ML experiment tracking, versioning, and deployment using MLflow.
- Automate model training, evaluation, and deployment workflows.
- Collaborate with data scientists, data engineers, and cloud architects to integrate ML solutions into production systems.
- Migrate existing models into AWS environments and ensure performance improvements.
- Monitor model drift, manage retraining processes, and improve model lifecycle management.
- Ensure adherence to best practices in code quality, CI/CD, and MLOps governance.
- 8 9 years of overall experience with at least 5 years in applied machine learning and model deployment.
- Strong hands-on experience with AWS SageMaker for training and deploying ML models.
- Proficiency in Python, PySpark, and relevant data science libraries (Pandas, NumPy, Scikit-learn).
- Expertise with MLflow for model tracking, registry, and lifecycle management.
- Strong experience in Terraform for infrastructure automation.
- Solid understanding of machine learning principles, data preprocessing, and scalable feature engineering.
- Experience with CI/CD pipelines, container orchestration (Docker, ECS, EKS), and version control systems (Git).
- Excellent problem-solving, communication, and collaboration skills.
- Bachelor s or master s degree in computer science, Data Science, or related field.