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Salary: USD 170,000 - 225,000 / annual
Taskrabbit is a marketplace platform connecting people with Taskers for everyday home services like furniture assembly, handyman work, and moving help. The company is owned by IKEA and operates as a hybrid organization with employees across the US and EU.
You will join as a Staff Machine Learning Engineer focused on customer retention and lifetime value growth. This is a full-stack role owning the complete ML lifecycle—from research and model development through production deployment, monitoring, and optimization.
Key responsibilities include:
• Owning the core Taskrabbit ranking model that powers tasker-to-job matching and optimizes First-Time Right (FTR) rates
• Driving increased repeat purchase frequency through intelligent matching, personalized recommendations, and category discovery
• Expanding customer lifetime value by helping customers find and return for new service categories
• Optimizing affordability and relevance via dynamic pricing, smart segmentation, and category-specific experiences
• Reducing friction and churn through predictive quality interventions and proactive customer success
• Building and maintaining scalable, reliable ML infrastructure and data pipelines supporting reproducible feature engineering and model deployment across real-time, near real-time, and batch contexts
• Developing monitoring and observability systems to understand data quality and model performance in complex systems
• Writing clean, efficient, maintainable code and participating actively in code reviews and best practices
The role is hybrid, requiring 2 days in office (Tuesdays & Wednesdays) at either the San Francisco or NYC hub.
REQUIREMENTS:
• BS, MS, or PhD in Computer Science, Statistics, Operations Research, or related quantitative field
• 8+ years of industry experience building and deploying production-grade machine learning models and systems
• Strong theoretical knowledge and hands-on experience in machine learning, particularly in search, ranking, recommender systems, pricing/elasticity modeling, or predictive analytics
• Solid software engineering skills with proficiency in Python and popular ML libraries (Scikit-learn, LightGBM, XGBoost, TensorFlow, PyTorch)
• Proficiency in SQL for writing complex queries and data transformation
• Experience building REST API-based services
• Experience with modern data and ML technologies: Docker, Kubernetes, Kafka, Airflow, data warehouses (Snowflake, Redshift, BigQuery), and data lakes
• Familiarity with dbt for data transformation and testing (plus)
• Familiarity with Infrastructure as Code tools such as Github Actions and CI/CD pipelines
• Excellent communication skills to present complex findings to technical and non-technical audiences
• Passion for learning new technologies and solving challenging problems with a collaborative mindset
• Ideally, experience working in marketplace or platform contexts where ranking, matching, and pricing directly impact user experience and business outcomes
