Staff ML Engineer: Retention & Ranking for Growth

Taskrabbit; San Francisco (CA); Hybrid; USD 170,000 - 225,000; Full time

Benefits offered by this job

Health insurance

401k match

Generous time off with company closure

Product stipends

Wellness stipend

IKEA discounts

Reproductive health support

Job summary

Taskrabbit is seeking a Staff Machine Learning Engineer to lead the next phase of our customer retention strategy. You will own the end-to-end ML lifecycle, from research to production, focusing on repeat engagement and lifetime value at scale.

The role blends research, software engineering, and infrastructure to deliver robust, scalable models. As a core member of the team, you will drive ranking, recommendations, pricing, and category expansion while collaborating across engineering and data

Qualifications

• BS, MS, or PhD in Computer Science, Statistics, Operations Research, or a related quantitative field.
• 8+ years of industry experience building and deploying high-quality, production-grade ML models and systems.
• Strong theoretical knowledge and hands-on experience in ML, particularly in search, ranking, recommender systems, pricing/elasticity modeling, or predictive analytics.
• Proficiency in SQL and Python; experience with popular ML libraries like Scikit-learn, lightgbm, xgboost, TensorFlow, PyTorch, etc.
• Experience building REST API-based services.
• Experience with modern data/ML tech: Docker, Kubernetes, Kafka, Airflow, data warehouses (Snowflake, Redshift, BigQuery) and data lakes.
• Familiarity with dbt is a plus.
• Familiarity with IaC tools like GitHub Actions and CI/CD pipelines.
• Excellent communication skills and collaborative mindset.
• Experience in marketplace/platform contexts with ranking, matching, and pricing.

Responsibilities

• Own the reliability and performance of Taskrabbit's core ranking system and optimize First-Time Right rates.
• Increase repeat purchase frequency through intelligent matching, personalized recommendations, and category discovery.
• Expand customer lifetime value by helping customers find and return for new service categories.
• Optimize affordability and relevance via dynamic pricing, segmentation, and category-specific experiences.
• Reduce friction and churn through predictive quality interventions and proactive customer success.
• Build systems for marketplace resilience to keep high-value customers engaged and loyal.
• Own the end-to-end ML lifecycle from feature engineering to deployment, monitoring, and optimization.
• Develop scalable ML infrastructure and data pipelines for real-time, near real-time, and batch contexts.
• Create monitoring/observability to understand data quality and model performance; collaborate with teams to optimize training/inference/evaluation.
• Write clean, efficient code and participate in code reviews and best practices across the software lifecycle.

Skills

Python

SQL

REST APIs

Docker

Kubernetes

Scikit-learn

TensorFlow/PyTorch

Education

CS/Stats degree

Tools

Snowflake/Redshift/BigQuery

Airflow

dbt

Job description

Taskrabbit is seeking a Staff Machine Learning Engineer to lead the next phase of our customer retention strategy. You will own the end-to-end ML lifecycle, from research to production, focusing on repeat engagement and lifetime value at scale.

The role blends research, software engineering, and infrastructure to deliver robust, scalable models. As a core member of the team, you will drive ranking, recommendations, pricing, and category expansion while collaborating across engineering and data