Machine Learning Engineer

Apply machine learning expertise to help train and improve next-generation AI systems through high-quality, real-world technical input. Key Responsibilities

• Design, develop, and refine machine learning models in Python to meet project objectives.
• Analyze large datasets and use MongoDB to manage and retrieve data for training and validation.
• Collaborate with cross-functional contributors to identify model improvements and implement robust solutions.
• Evaluate models, tune hyperparameters, and benchmark results to support strong performance.
• Document methodologies, experiments, and outcomes to create transparent, repeatable workflows.
• Integrate data pipelines and preprocessing workflows for efficient training and inference.
• Deliver actionable recommendations based on data-driven findings and machine learning outcomes.

• Strong Python expertise and familiarity with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch.
• Hands-on MongoDB experience for data manipulation, storage, and retrieval in machine learning projects.
• Strong problem-solving ability and a record of delivering practical, innovative machine learning solutions.
• Knowledge of model evaluation metrics, feature engineering, and data preprocessing techniques.
• Experience deploying or operationalizing machine learning models in cloud or enterprise environments is preferred.
• Clear written documentation and communication skills.
• Ability to adapt to changing project requirements and collaborate effectively in a remote setting.

• Remote contract engagement.

• $80 to $140 per hour.

• Submit an application using an email address or a Google account.