Machine Learning Engineer

Machine Learning Engineer

Remote | Contractor | $80–$140/hour Annualized Equivalent: $166,400–$291,200/year based on 40 hours/week About The Role We are looking for experienced Machine Learning Engineers to contribute their expertise to a dynamic project focused on training next-generation AI systems.

In this role, you will apply your machine learning and software engineering skills to help develop high-quality training inputs and improve how AI systems learn, reason, and perform. You will work with real-world data, develop and evaluate machine learning models, and contribute to robust workflows for model training and inference.

This opportunity is well suited to engineers with strong Python, machine learning, and MongoDB experience who enjoy solving complex technical problems and working collaboratively in a remote environment.

What You’ll Do

Machine Learning Development

• Design, develop, and refine machine learning models using Python and relevant libraries.
• Build solutions that address project objectives and evolving technical requirements.
• Apply machine learning expertise to improve model performance and outcomes.
• Develop robust solutions based on real-world data and project requirements.

Data & MongoDB

• Analyze large datasets to identify relevant patterns and insights.
• Use MongoDB to efficiently manage, manipulate, store, and retrieve data.
• Support data workflows used for model training and validation.
• Integrate data pipelines and preprocessing workflows to streamline training and inference processes.

Model Evaluation & Optimization

• Conduct thorough evaluation of machine learning models.
• Tune model hyperparameters to improve performance.
• Benchmark model results and compare performance across approaches.
• Apply appropriate evaluation metrics to assess model quality and effectiveness.
• Use data-driven findings to identify opportunities for model improvement.

Collaboration & Documentation

• Collaborate with cross-functional contributors to identify areas for model improvement.
• Implement robust machine learning solutions based on project needs.
• Document methodologies, experiments, and outcomes.
• Maintain transparent and repeatable technical workflows.
• Deliver actionable insights and recommendations based on data-driven findings and machine learning outcomes.
• Communicate technical findings and best practices clearly.

Preferred Qualifications

• Demonstrated expertise with Python.
• 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 machine learning 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.
• Strong written documentation and communication skills.
• Ability to clearly communicate technical findings and best practices.
• Ability to adapt quickly to evolving project requirements.
• Ability to contribute effectively and collaboratively in a remote setting.

Ideal Candidate

The ideal candidate combines strong machine learning engineering expertise with practical experience working with Python, machine learning frameworks, large datasets, and MongoDB .

You should be comfortable developing and refining models, evaluating and tuning performance, building reliable data workflows, documenting experiments, and translating machine learning outcomes into actionable insights.

If you enjoy solving challenging machine learning problems and contributing your technical expertise to the development and improvement of next-generation AI systems, this role offers an opportunity to apply your skills to meaningful, real-world work.