Machine Learning Engineer

EVB

WorldwideFully remoteContractMid LevelInformation Technology
Posted 2w ago

Why we think you can apply

Hiring model
Open worldwide · the employer states no country restriction
Work from
Anywhere, the UAE included

Posted 14 days ago · apply link checked 8 hours ago

About the role

Responsibilities

  • 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

Requirements

  • Demonstrated expertise with Python, including deep familiarity with machine learning frameworks such asscikit-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

About the Company

EVB is a venture-backed AI company helping shape the next generation of intelligent systems by combining human expertise with advanced machine learning workflows. Backed by more than $40 million in funding, the organization is building critical human intelligence infrastructure for the AI economy.

What we look for

  • Python
  • Machine learning frameworks
  • MongoDB
  • Model evaluation
  • Data preprocessing
PythonMongoDBPyTorchTensorFlowscikit-learn
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