Machine Learning Engineer
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M1
Micro1Software Engineering

Machine Learning Engineer

Remote$80 - 140/hrContract / Freelance

About the Role

micro1 is engaging Machine Learning Engineers to contribute expertise to a dynamic customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.


Responsibilities & Tasks

  • 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.

Qualifications & Requirements

  • 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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