Machine Learning Engineer

Machine Learning Engineer / AI Specialist Long Term Contract (High Likelihood Of Extension or Conversion) Rate: $60-65/hr (DOE) Hybrid (3x on-site) - Charlotte, NC We are seeking a Machine Learning Engineer / AI Specialist to design, build, and scale machine learning solutions in a cloud-based environment. This role focuses on taking models from development through production while applying strong MLOps practices to ensure reliability, performance, and automation. You will collaborate closely with data scientists, engineers, and platform teams to deploy robust ML systems and continuously improve model operations. Key Responsibilities • Design, develop, and deploy machine learning models using AWS SageMaker • Build and maintain ML pipelines for training, validation, and deployment • Implement MLOps best practices, including CI/CD for ML workflows • Partner with data scientists to productionize research models • Monitor model performance and automate retraining processes • Optimize inference performance and cloud cost efficiency • Manage model versioning and experiment tracking • Ensure data quality through validation frameworks • Maintain infrastructure using Terraform and DevOps tooling • Debug pipeline and infrastructure issues as they arise • Migrate repositories and modernize CI/CD pipelines as needed • Create clear technical documentation and standards Required Qualifications • Bachelor’s degree in Computer Science, Engineering, Data Science, or equivalent experience • 3+ years of experience in machine learning engineering or related roles • Strong Python skills and experience with ML libraries (pandas, numpy, etc.) • Hands-on experience with AWS SageMaker • Experience with Infrastructure as Code (Terraform preferred) • Solid foundation in data science and statistical concepts • Strong understanding of MLOps tools and workflows (CI/CD, Docker, Kubernetes) • Experience using Git-based version control systems • Familiarity with AWS services such as S3, EC2, Lambda Preferred Qualifications • Master’s degree in a related field • AWS certifications • Experience with monitoring and observability tools • Exposure to big data platforms (EMR, Spark, Hadoop) • Strong SQL skills and ETL experience • Experience with container orchestration technologies • Knowledge of basic ML model development (classification and regression) Key Skills & Competencies • Strong problem-solving and analytical abilities • Clear communication and collaboration skills • Comfort working in fast-paced environments • High standards for code quality and documentation • Continuous learning mindset • Experience working cross-functionally with technical teams Disclaimer: Brooksource, Medasource, and Calculated Hire are part of the Eight Eleven Group family of companies and operate under Eight Eleven Group, LLC. All employees receive the same benefits, policies, and terms of employment. EEO: We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, creed, sex, sexual orientation, gender identity or expression, national origin, ancestry, age, disability, genetic information, marital status, military or veteran status, citizenship, pregnancy (including childbirth, lactation, and related conditions), or any other protected status in accordance with applicable federal, state, and local laws. Benefits & Perks: Brooksource offers competitive medical, dental, vision, Health Savings Account, Dependent Care FSA, and supplemental coverage with plans that can fit each employee’s needs. We offer a 401k plan that includes a company match and is fully vested after you become eligible, paid time off, sick time, and paid company holidays. We also offer an Employee Assistance Program (EAP) that provides services like virtual counseling, financial services, legal services, life coaching, etc. Pay Disclaimer: The pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.