Staff Machine Learning Engineer - Retention

Responsibilities

• Own the reliability and performance of Taskrabbit’s core tasker-to-job ranking system and optimize First-Time Right rates.
• Develop intelligent matching, personalized recommendations, category discovery, dynamic pricing, segmentation, and predictive quality or churn interventions to increase repeat purchases and customer lifetime value.
• Own models end to end, including feature engineering, training, evaluation, deployment, monitoring, and production optimization.
• Build scalable ML infrastructure and data pipelines supporting reproducible feature engineering and real-time, near-real-time, and batch model deployment.
• Develop monitoring and observability systems for data quality and model performance, and optimize training, inference, and evaluation algorithms.
• Write maintainable software and contribute to code reviews, documentation, and software engineering best practices.

Requirements

• BS, MS, or PhD in Computer Science, Statistics, Operations Research, or a related quantitative field.
• 8+ years of industry experience building and deploying production-grade machine learning models and systems.
• Strong machine learning expertise in areas such as search, ranking, recommender systems, pricing or elasticity modeling, and predictive analytics.
• Strong software engineering skills with proficiency in one or more programming languages, including Python.
• Experience with Scikit-learn, LightGBM, XGBoost, TensorFlow, or PyTorch.
• Proficiency in SQL for complex queries and data transformation.
• Experience building REST API-based services.
• Experience with Docker, Kubernetes, Kafka, Airflow, data warehouses such as Snowflake, Redshift, or BigQuery, and data lakes.
• Familiarity with dbt, GitHub Actions, and CI/CD pipelines is a plus.
• Excellent communication skills and the ability to present complex findings to technical and non-technical audiences.
• Marketplace or platform experience with ranking, matching, or pricing is preferred.

Benefits

• Hybrid work requiring two days in the San Francisco or New York City office every Tuesday and Wednesday.
• Employer-paid health insurance and a 401(k) match with immediate vesting for US-based employees.
• Generous and flexible time off for global employees, including two company-wide closure weeks.
• Taskrabbit product stipends, wellness, productivity, and education stipends, IKEA discounts, and reproductive health support.
• Benefits vary by country of employment.