Senior Machine Learning Engineer

• Design, develop, and deploy production machine learning models that power core product experiences and decision-making systems
• Own the end-to-end machine learning lifecycle, including data analysis, feature engineering, model training, evaluation, deployment, and monitoring
• Partner closely with Product, Engineering, Data, and Operations to translate product requirements and business goals into scalable ML solutions
• Develop experimentation frameworks and causal measurement strategies to evaluate model impact and inform product decisions
• Build and maintain forecasting, ranking, personalization, or optimization systems operating at scale
• Drive improvements to model performance, reliability, and scalability in production environments
• Contribute to the ML platform and infrastructure, improving tooling for training, experimentation, and monitoring
• Influence technical direction through design reviews, code reviews, and mentorship of other engineers

• 5+ years of industry experience building and deploying machine learning systems in production
• Strong proficiency in Python and experience with common ML frameworks and libraries (e.g., PyTorch, TensorFlow, XGBoost, LightGBM, scikit-learn)
• Experience owning the full ML lifecycle, from data exploration to production deployment and iteration
• Experience working with large-scale, real-world datasets and noisy or incomplete data
• Solid understanding of experiment design and causal inference, including A/B testing and offline evaluation
• Ability to collaborate effectively with cross-functional partners and communicate technical concepts clearly
• Bachelor’s degree in Computer Science, Engineering, Statistics, or a related field, or equivalent practical experience

Offers Equity