🌍 Machine Learning Engineer, Remote - Contract
Xperteez Technology United States · $166K–$291K/yr
Business Consulting and Services · 51-200 employees
About the role
Design, develop, and refine machine learning models while managing large datasets using MongoDB. Collaborate with cross-functional teams to evaluate model performance and integrate efficient data pipelines.
What they look for
Requirements
Requires demonstrated expertise in Python and machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch. Candidates must have hands-on experience with MongoDB and strong problem-solving skills for real-world ML applications.
Full description
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.
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