About this opportunity
Confidential lists this Machine Learning Engineer opportunity in raleigh, North Carolina. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Role Overview
Apply machine learning expertise to help train next-generation AI systems through high-quality, real-world input that improves how models learn, reason, and perform.
Key Responsibilities
Design, develop, and refine machine learning models in Python using relevant libraries.
Analyze large datasets and use MongoDB to manage and retrieve training and validation data efficiently.
Partner with cross-functional contributors to identify model improvements and implement robust solutions.
Evaluate models, tune hyperparameters, and benchmark results to support strong performance.
Document methodologies, experiments, and outcomes to create transparent, repeatable workflows.
Integrate data pipelines and preprocessing workflows for training and inference.
Deliver actionable recommendations based on data-driven findings and machine learning outcomes.
Qualifications
Strong Python skills and familiarity with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch.
Hands-on MongoDB experience for data manipulation, storage, and retrieval in machine learning projects.
Knowledge of model evaluation metrics, feature engineering, and data preprocessing techniques.
Strong problem-solving skills and experience delivering practical machine learning solutions.
Experience deploying or operationalizing machine learning models in cloud or enterprise environments is preferred.
Clear written documentation and communication skills.
Ability to adapt to changing project requirements and collaborate effectively in a remote environment.
Work Terms
Remote contract engagement.
Compensation
$80 to $140 per hour.
Application Process
Apply using an email address or a Google account. Submission is subject to the applicable terms and privacy policies.
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.