Machine Learning Engineer

Stack

Responsibilities

• ▹Design, develop and refine machine learning models using Python and relevant libraries
• ▹Analyze large datasets and use MongoDB to manage and retrieve data for model training and validation
• ▹Collaborate with cross-functional contributors to identify model improvements and implement robust solutions
• ▹Evaluate models, tune hyperparameters and benchmark results for optimal performance
• ▹Document methodologies, experiments and outcomes for transparent and repeatable workflows
• ▹Integrate data pipelines and preprocessing workflows to streamline training and inference
• ▹Deliver actionable insights and recommendations based on data-driven findings

Nice to have

• ▹Demonstrated Python expertise, deep familiarity with ML frameworks such as scikit-learn, TensorFlow or PyTorch
• ▹Hands-on MongoDB experience for data manipulation, storage and retrieval in ML projects
• ▹Strong problem-solving skills and a track record of delivering ML solutions in real-world settings
• ▹Understanding of model evaluation metrics, feature engineering and data preprocessing
• ▹Background in deploying or operationalizing ML models in cloud or enterprise environments
• ▹Clear written documentation and communication skills
• ▹Ability to adapt quickly to evolving requirements in a remote setting

Soft skills

What we offer

• ▹Remote work
• ▹Contractor engagement
• ▹Competitive package

About the company

The client is a rapidly growing, venture-backed AI company that combines human expertise with machine learning workflows to help leading AI organizations build, evaluate and improve models. It has raised over $40 million and has an international expert network.