Machine Learning Engineer | Remote - Contract

Role Title

Machine Learning Engineer

Role Type

Contract

Location

Remote

We are engaging Machine Learning Engineers to contribute expertise to a dynamic customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.

Required Skills

• Python
• Machine Learning
• MongoDB

Scope of Work

• Design, develop, and refine machine learning models using Python and relevant libraries to address project objectives.
• Analyze large datasets and leverage MongoDB to manage and retrieve data efficiently for model training and validation.
• Collaborate with cross-functional contributors to identify areas for model improvement and implement robust solutions.
• Conduct thorough model evaluation, tuning hyperparameters, and benchmarking results to ensure optimal performance.
• Document methodologies, experiments, and outcomes to ensure transparent and repeatable workflows.
• Integrate data pipelines and preprocessing workflows to streamline training and inference processes.
• Deliver actionable insights and recommendations based on data-driven findings and machine learning outcomes.

Preferred Qualifications

• Demonstrated expertise with Python, including 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 ML 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.
• Clear written documentation and communication skills for sharing technical findings and best practices.
• Ability to adapt quickly to evolving project requirements and contribute collaboratively in a remote setting.