Machine Learning Engineer (Python)

You will develop and improve machine learning models that support AI training and model evaluation. The work includes analyzing real-world datasets, preparing data, training models, testing results, and documenting your methods.

You will also help improve data pipelines and model inference workflows, share technical recommendations, and work with other contributors on practical machine learning solutions.

• Build and refine machine learning models with Python and established libraries.
• Analyze large datasets and use MongoDB for storage, retrieval, manipulation, training, and validation.
• Evaluate models, tune hyperparameters, benchmark results, and identify areas for improvement.
• Create preprocessing and data pipeline workflows for model training and inference.
• Document experiments, methods, results, and technical best practices.
• Collaborate with contributors and provide useful findings from machine learning results.

This is a remote, part-time contractor opportunity for an individual contributor.

• Pay: $80 to $140 per hour.
• Work arrangement: Remote contractor role with part-time work.
• Language: Professional fluency in English.
• Location: Open to candidates in the United Arab Emirates, Argentina, Austria, Bangladesh, Belgium, Bahrain, Brazil, Canada, Switzerland, Chile, Colombia, Germany, Denmark, Algeria, Egypt, Spain, France, the United Kingdom, Ghana, Greece, Indonesia, India, Italy, Jordan, Japan, Kenya, Kyrgyzstan, Kuwait, Kazakhstan, Lebanon, Sri Lanka, Morocco, Mexico, Malaysia, Nigeria, the Netherlands, Oman, Peru, the Philippines, Pakistan, Palestine, Portugal, Qatar, Saudi Arabia, Singapore, Thailand, Tunisia, Taiwan, the United States, Uzbekistan, Vietnam, and South Africa.
• Technical skills: Strong Python development and familiarity with scikit-learn, TensorFlow, or PyTorch.
• Data skills: Hands-on MongoDB experience in machine learning or data-focused projects.
• Machine learning knowledge: Model evaluation metrics, feature engineering, and data preprocessing.
• Other requirements: Problem-solving ability, practical machine learning delivery experience, and clear technical documentation.
• Helpful background: Deploying or operationalizing machine learning models in cloud or enterprise environments, adapting to changing requirements, and collaborating remotely.

You apply here in about two minutes and finish on the hiring platform. The next step is a short AI interview (technical roles include a coding challenge). Passing it is how you qualify for paid tasks, so take it soon after you are invited.

The hiring platform's application for this job asks for your resume, your LinkedIn profile, your phone number, your location and answers to 3 screening questions.

AI training work is the human side of building artificial intelligence. People prepare data, test models, and review results so AI systems can learn from better examples, and experienced contributors are needed for technical work such as machine learning development and evaluation.