Machine Learning Model Development Engineer

About OpenTrain

OpenTrain AI is the #1 platform for finding and building careers in AI training and data labeling. For this opportunity, OpenTrain is hiring a remote contractor to support practical machine learning development and help improve the reliability of real-world AI systems.

Creating an OpenTrain account is free, and contributors can build a profile that showcases their AI training and technical experience while applying to relevant projects.

• Remote contractor opportunity
• Part-time engagement with a 20+ hour weekly commitment
• Advertised compensation of $80-$140 per hour

About AI Training and Machine Learning Work

AI training is the human side of building artificial intelligence. People help AI systems learn by preparing data, evaluating results, writing and reviewing code, and testing whether models produce reliable outputs.

Machine learning engineers contribute at the technical end of this process by preparing large datasets, developing models, measuring performance, and turning experimental findings into improvements that support effective training and inference workflows.

• Work at the intersection of software engineering, data analysis, and AI development
• Contribute to how modern AI systems are trained and evaluated
• Use structured experimentation and human judgment to improve model performance

The Machine Learning Model Development Engineer Role

OpenTrain is recruiting a Machine Learning Model Development Engineer for a remote contractor project supporting AI training through model development, data analysis, validation, and performance improvement. You will work with Python, machine learning frameworks, MongoDB, large datasets, preprocessing workflows, and model evaluation methods.

The role combines hands-on engineering with careful experimentation, technical documentation, and data-driven recommendations. You will also collaborate with cross-functional contributors and adapt to evolving project requirements in a remote setting.

• Develop and refine machine learning models for project objectives
• Analyze large datasets used for training and validation
• Support reliable, repeatable workflows for real-world AI systems

What You'll Do

You will take machine learning projects from data preparation and experimentation through evaluation and documented recommendations. The work requires practical judgment across modeling, data handling, validation, and performance improvement.

• Design, develop, and refine machine learning models with Python and relevant libraries.
• Use MongoDB to manage, manipulate, store, and retrieve data for machine learning projects.
• Integrate data pipelines and preprocessing workflows to streamline training and inference processes.
• Evaluate models, tune hyperparameters, and benchmark results to assess performance.
• Identify areas for model improvement and implement robust solutions collaboratively.
• Document methodologies, experiments, and outcomes to support transparent and repeatable workflows.
• Deliver actionable insights and recommendations based on data-driven findings and machine learning outcomes.

Required Skills and Experience

This opportunity is listed at the entry level, while the project requirements call for advanced practical capabilities in machine learning development. Applicants should be prepared to demonstrate hands-on experience delivering machine learning solutions in real-world settings.

• Advanced Python development for machine learning workflows.
• Strong familiarity with scikit-learn, TensorFlow, or PyTorch.
• Hands-on experience with MongoDB data manipulation, storage, and retrieval in ML projects.
• Understanding of model evaluation metrics, feature engineering, and effective data preprocessing techniques.
• Strong problem-solving skills and the ability to deliver machine learning solutions.
• Clear written documentation and communication skills for sharing technical findings and best practices.
• Ability to collaborate remotely and adapt to evolving project requirements.

Helpful Background

Experience deploying or operationalizing machine learning models in cloud or enterprise environments is helpful, particularly when paired with experience connecting data pipelines to production-oriented training and inference workflows.

• Model deployment or operationalization experience
• Exposure to cloud or enterprise machine learning environments
• Experience connecting data pipelines to production-oriented workflows

Schedule, Location, and Compensation

This is a worldwide remote contractor opportunity with a part-time commitment of 20 or more hours per week. The working language is English.

• Location: Worldwide and remote
• Time requirement: 20+ hours per week
• Employment type: Contractor and part-time
• Language: English
• Advertised pay: $80-$140 per hour

Build Your AI Career with OpenTrain

AI training and data-labeling work is a fast-growing way to work in tech from anywhere with a computer or phone and an internet connection. Specialist projects such as machine learning engineering can let experienced contributors apply valuable technical knowledge while helping shape state-of-the-art AI systems.

OpenTrain helps contributors find opportunities, build a professional profile, and grow a durable career in AI training and data labeling. Apply through OpenTrain to put your machine learning skills to work on a flexible remote project.

• Work remotely on cutting-edge AI development
• Build a profile around your machine learning experience
• Create a foundation for long-term growth in AI training