Remote | Machine Learning Engineer — $80–$140/hour
About The Position
This remote independent-contractor consulting engagement involves contributing to an advanced AI training and machine learning project. The Machine Learning Engineer will design and refine models, work with large datasets, build preprocessing and data pipelines, and evaluate model performance through experimentation and benchmarking. The work calls for practical machine learning expertise, structured technical reasoning, and clear documentation of methods and findings. Project scope, workload, technical requirements, and evaluation criteria may evolve with project needs. Work must not use confidential or proprietary information belonging to any employer, client, institution, or other third party. The opportunity is available through 24-MAG LLC, which connects experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams. Application information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with its Privacy Policy.
Requirements
- Demonstrated professional expertise in Python.
- Strong experience with machine learning frameworks such as scikit-learn, TensorFlow, PyTorch, or comparable tools.
- Hands-on experience using MongoDB for data storage, retrieval, and manipulation.
- Strong understanding of machine learning fundamentals and model-development workflows.
- Familiarity with model evaluation metrics, hyperparameter tuning, and benchmarking.
- Practical experience with feature engineering and data preprocessing.
- Strong problem-solving ability and experience delivering real-world machine learning solutions.
- Experience developing or integrating data pipelines for machine learning workflows.
- Strong written documentation and technical communication skills.
- Ability to work effectively in a remote and evolving project environment.
Nice To Haves
- Background deploying or operationalising machine learning models in cloud or enterprise environments.
- Experience deploying or operationalising machine learning systems is highly valued.
Responsibilities
- Design, develop, and refine machine learning models using Python and relevant frameworks.
- Select modelling approaches based on project objectives and available data.
- Implement robust model training and validation workflows.
- Apply feature engineering and data-preparation techniques where appropriate.
- Improve model quality through iterative experimentation and analysis.
- Evaluate models systematically using appropriate performance metrics.
- Tune hyperparameters to improve model effectiveness and stability.
- Benchmark alternative models, configurations, and approaches.
- Identify model weaknesses, failure patterns, and opportunities for improvement, supporting conclusions with reproducible experimental results.
- Analyse and work with large datasets used for model training and validation.
- Use MongoDB for data storage, retrieval, and manipulation.
- Develop preprocessing workflows and integrate data pipelines across training and inference processes.
- Identify and resolve data-quality or pipeline issues that affect model performance.
- Document methodologies, experiments, assumptions, and outcomes clearly.
- Maintain transparent and repeatable machine learning workflows.
- Collaborate with cross-functional contributors to identify model-improvement opportunities.
- Communicate technical findings and recommendations clearly and actionably.
- Adapt modelling approaches as project requirements evolve.
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What This Job Offers
Education Level
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