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Salary: USD 170,000 - 225,000 / annual
Taskrabbit is a marketplace platform connecting people with Taskers for home services like furniture assembly, handyman work, and moving help. The company is owned by IKEA and operates across the US and EU with a hybrid work culture.
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 Taskrabbit's core ranking model, ensuring accurate tasker-to-job matching and optimizing First-Time Right (FTR) rates
• Driving 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, and maintainable code with active participation 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 one or more additional programming languages
• Experience with ML libraries: Scikit-learn, LightGBM, XGBoost, TensorFlow, PyTorch, or similar
• Proficiency in SQL for 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 (preferred)
• Familiarity with Infrastructure as Code tools such as Github Actions and CI/CD pipelines
• Excellent communication skills for presenting complex findings to technical and non-technical audiences
• Passion for learning new technologies and solving challenging problems with a collaborative mindset
• Ideally, experience in marketplace or platform contexts where ranking, matching, and pricing directly impact user experience and business outcomes
