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Xperteez Technology / Datos

Machine Learning Engineer, Remote - Contract

nuevaDesde Argentina

  • Remoto desde Argentina
  • Contrato
  • Remoto
  • Senior

Requisitos

  • python
  • machine learning
  • mongodb
  • • inglés intermedio o más (el aviso está escrito en inglés)

Suma si tenés

  • comunicación

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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.

Originally posted on Himalayas

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