Staff ML Engineer: End-to-End ML for Growth & Retention

Taskrabbit; San Francisco (CA); Hybrid; USD 175,000 - 230,000; Full time

Benefits offered by this job

Employer-paid health insurance

401k match

Generous time off

IKEA discounts

Product stipends

Job summary

Taskrabbit is seeking a Staff Machine Learning Engineer to lead our customer retention strategy. This full-time, hybrid role combines research, model development, and building scalable systems to improve repeat engagement and lifetime value at scale.

You will own the end-to-end ML lifecycle—from feature engineering and training to deployment, monitoring, and optimization—working with Python, SQL, and modern ML tools.

Qualifications

• 8+ years of industry experience building and deploying production ML models and systems.
• Strong knowledge in search, ranking, recommender systems, pricing/elasticity modeling, or predictive analytics.
• Proficiency in Python and SQL.
• Experience with REST APIs and modern data technologies (Docker, Kubernetes, Kafka, Airflow, Snowflake/Redshift/BigQuery).
• Excellent communication and collaboration skills.

Responsibilities

• Own the Taskrabbit Ranking Model for reliable tasker-to-job matching and First-Time Right.
• Increase repeat purchase frequency through intelligent matching and personalized recommendations.
• Expand customer lifetime value by promoting new service categories.
• Improve affordability and relevance with dynamic pricing and segmentation.
• Reduce churn with predictive quality interventions and proactive customer success.
• Build scalable ML infrastructure and data pipelines across real-time and batch contexts.
• Own end-to-end ML lifecycle from feature engineering to deployment.
• Collaborate with engineering and data teams to monitor models and data quality.

Skills

Ranking model

Recommender systems

Python

SQL

ML deployment

Communication skills

Education

BS/MS/PhD in CS or related

Tools

TensorFlow

PyTorch

Scikit-learn

Docker

Kubernetes

Airflow

Job description

Taskrabbit is seeking a Staff Machine Learning Engineer to lead our customer retention strategy. This full-time, hybrid role combines research, model development, and building scalable systems to improve repeat engagement and lifetime value at scale.

You will own the end-to-end ML lifecycle—from feature engineering and training to deployment, monitoring, and optimization—working with Python, SQL, and modern ML tools.