SeniorMachineLearningEngineer

## Accountabilities You will lead the design, development, and deployment of machine learning systems that power personalization, search, and marketplace optimization. You will work across the full ML lifecycle—from data exploration and modeling to productionization and monitoring—while partnering closely with cross-functional teams to align technical solutions with business needs. Design and improve recommendation, ranking, and search systems to enhance product discovery and user engagement Develop and deploy ML models for personalization, inventory valuation, classification, and demand forecasting Build and maintain scalable data models and pipelines using Snowflake and Python-based workflows Own experimentation frameworks, including A/B testing, KPI definition, and performance evaluation of ML systems Deploy models into production environments and ensure reliability, observability, and version control best practices Collaborate with Product, Engineering, Design, and Marketing teams to translate business needs into data-driven solutions Develop advanced analytics capabilities such as embeddings, user-to-item mapping, and fraud detection signals Continuously improve model performance through iteration, monitoring, and optimization of data and features Requirements: The ideal candidate brings extensive experience building and scaling machine learning systems in production, particularly in consumer-facing or marketplace environments. You combine strong theoretical foundations in statistics and ML with practical engineering skills and a product-oriented mindset. 8+ years of experience in machine learning, data science, or quantitative engineering roles Expert-level proficiency in Python for ML model development and data manipulation Strong experience with SQL and data warehousing environments such as Snowflake Deep understanding of recommendation systems, ranking models, and personalization techniques Experience with causal inference, experimentation design, and stati