Micro 1
$80–140/hr
35 people hired
Machine Learning Engineers to contribute technical expertise to a remote AI-training project focused on improving next-generation AI systems. The role involves building and refining machine learning models, working with large datasets, managing data through MongoDB, and developing reliable preprocessing and training workflows. Engineers will evaluate model performance, tune hyperparameters, benchmark results, and document experiments to ensure transparent and reproducible outcomes. This opportunity is ideal for professionals with strong Python, machine learning, MongoDB, and real-world model-development experience.
Machine Learning AI Engineer
Design, develop, and refine machine learning models using Python and relevant ML frameworks to meet project objectives. | Analyze large datasets and use MongoDB for efficient data storage, retrieval, and model-training workflows. | Evaluate models, tune hyperparameters, benchmark performance, and identify opportunities for improvement. | Build preprocessing and data pipelines that streamline model training and inference. | Document methodologies, experiments, results, and actionable recommendations while collaborating with cross-functional contributors.
Strong proficiency in Python with hands-on experience using machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch. | Practical experience with MongoDB for data manipulation, storage, querying, and retrieval in machine learning projects. | Strong understanding of model evaluation metrics, feature engineering, preprocessing, hyperparameter tuning, and machine learning fundamentals. | Experience developing or deploying machine learning solutions in real-world, cloud, or enterprise environments. | Strong problem-solving, technical documentation, communication, and adaptability skills for remote collaborative projects.
