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AI Trainer Jobs

Machine Learning Engineer

micro1 · 100% remote · Contract · Posted

Pay
$80–140/hr
Location
Worldwide
Languages
English
Hours
Flexible
Openings
35
Level
Expert
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Summary

Develop and refine machine learning models for a remote customer project that supports AI training. Work includes Python development, MongoDB data management, model evaluation, data pipelines, and documentation.

What you'll do

  • Design, develop, and refine machine learning models using Python.
  • Analyze large datasets and manage training and validation data with MongoDB.
  • Collaborate with contributors to improve models.
  • Evaluate models, tune hyperparameters, and benchmark results.
  • Document methods, experiments, and outcomes.
  • Integrate data pipelines and preprocessing workflows.
  • Provide insights and recommendations based on model results.

Requirements

  • Preferred: Python expertise and familiarity with scikit-learn, TensorFlow, or PyTorch.
  • Preferred: Hands-on MongoDB experience in machine learning projects.
  • Preferred: Problem-solving skills and experience delivering machine learning solutions.
  • Preferred: Knowledge of evaluation metrics, feature engineering, and data preprocessing.
  • Preferred: Experience deploying machine learning models in cloud or enterprise environments.
  • Preferred: Clear technical documentation and communication skills.
  • Preferred: Ability to adapt to changing requirements and collaborate remotely.

Skills

  • Python
  • Machine Learning
  • MongoDB

Full description

Role Title: Machine Learning Engineer

Role Type: Contractor

Location: Remote


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.


Scope of Work

  1. Design, develop, and refine machine learning models using Python and relevant libraries to address project objectives.
  2. Analyze large datasets and leverage MongoDB to manage and retrieve data efficiently for model training and validation.
  3. Collaborate with cross-functional contributors to identify areas for model improvement and implement robust solutions.
  4. Conduct thorough model evaluation, tuning hyperparameters, and benchmarking results to ensure optimal performance.
  5. Document methodologies, experiments, and outcomes to ensure transparent and repeatable workflows.
  6. Integrate data pipelines and preprocessing workflows to streamline training and inference processes.
  7. Deliver actionable insights and recommendations based on data-driven findings and machine learning outcomes.


Preferred Qualifications

  1. Demonstrated expertise with Python, including deep familiarity with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch.
  2. Hands-on experience with MongoDB for data manipulation, storage, and retrieval within machine learning projects.
  3. Strong problem-solving skills and a track record of delivering innovative ML solutions in real-world settings.
  4. Understanding of model evaluation metrics, feature engineering, and effective data preprocessing techniques.
  5. Background in deploying or operationalizing machine learning models in cloud or enterprise environments.
  6. Clear written documentation and communication skills for sharing technical findings and best practices.
  7. Ability to adapt quickly to evolving project requirements and contribute collaboratively in a remote setting.

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