All roles / AI & machine learning
Machine Learning Engineer
- Location
- Remote
- Pay listed by micro1
- $80–140 per hour
- Field
- AI & machine learning
- Type
- Remote
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Role description
Copied from micro1's job page on 9 October 2026. The live page on micro1 is the one that counts.
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
- 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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