Machine Learning Engineer

• Design, develop, and deploy production-grade machine learning models
• Build complete ML pipelines, including data preprocessing, modeling, evaluation, and deployment
• Collaborate with cross-functional teams to translate business needs into ML solutions
• Clearly communicate complex technical concepts to non-technical stakeholders
• Document models, methodology, and decisions to support transparency and reproducibility

• Demonstrated experience building and shipping machine learning models in production environments
• Advanced proficiency with scikit-learn and strong foundational knowledge across machine learning techniques, including: Regression, Classification, Clustering, Ensemble methods, Feature engineering, Model evaluation and validation
• Strong understanding of the full machine learning lifecycle: Data preparation, Model selection, Hyperparameter tuning, Validation, Deployment strategies
• Ability to explain concepts such as the bias–variance tradeoff, overfitting, gradient boosting, and other ML fundamentals in a clear and accessible way

You can open a notebook, build a model with scikit-learn, and articulate both how it works and why it works — in plain, straightforward language

• medical, vision, dental, and life and disability insurance
• eligible to enroll in our company 401(k) plan