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Xperteez Technology

🌍 Machine Learning Engineer, Remote - Contract

Posted a month ago
$80 - $140 per hour
2-5 years experience
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AI Summary

Design, develop, and refine machine learning models while managing large datasets using MongoDB. Collaborate with cross-functional teams to evaluate model performance and integrate efficient data pipelines.

Role Title: Machine Learning Engineer

Role Type: Contractor

Location: Remote

Required Skills:

  • Python

  • Machine Learning

  • MongoDB

Scope of Work:

  • Design, develop, and refine machine learning models using Python and relevant libraries to address project objectives.

  • Analyze large datasets and leverage MongoDB to manage and retrieve data efficiently for model training and validation.

  • Collaborate with cross-functional contributors to identify areas for model improvement and implement robust solutions.

  • Conduct thorough model evaluation, tuning hyperparameters, and benchmarking results to ensure optimal performance.

  • Document methodologies, experiments, and outcomes to ensure transparent and repeatable workflows.

  • Integrate data pipelines and preprocessing workflows to streamline training and inference processes.

  • Deliver actionable insights and recommendations based on data-driven findings and machine learning outcomes.

Preferred Qualifications:

  • Demonstrated expertise with Python, including deep familiarity with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch.

  • Hands-on experience with MongoDB for data manipulation, storage, and retrieval within machine learning projects.

  • Strong problem-solving skills and a track record of delivering innovative ML solutions in real-world settings.

  • Understanding of model evaluation metrics, feature engineering, and effective data preprocessing techniques.

  • Background in deploying or operationalizing machine learning models in cloud or enterprise environments.

  • Clear written documentation and communication skills for sharing technical findings and best practices.

  • Ability to adapt quickly to evolving project requirements and contribute collaboratively in a remote setting.

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