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$170,000 – $225,000
Listed on Taskrabbit’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
Lead machine learning efforts to increase customer retention and lifetime value at a two-sided marketplace, owning everything from ranking models and recommendation systems to the infrastructure that supports them at scale. This role suits experienced ML engineers who have shipped production systems and want to apply their expertise to core business problems in matching, pricing, and customer engagement.
Our summary, not Taskrabbit’s wording. The full posting is on their site.
Skills this role names
- Amazon Redshift
- Apache Airflow
- Apache Kafka
- CI/CD
- Dialectical Behavior Therapy (DBT)
- Docker
- GitHub Actions
- Google BigQuery
- Kubernetes
- Python
- PyTorch
- REST APIs
- scikit-learn
- Snowflake
- SQL
- TensorFlow
- XGBoost
Log in to see which of these are already on your profile.
What they ask for
Required
- BS, MS, or PhD in Computer Science, Statistics, Operations Research, or related quantitative field
- 8+ years industry experience building and deploying production machine learning models and systems
- Strong theoretical and hands-on machine learning knowledge, particularly in search, ranking, recommender systems, pricing/elasticity modeling, or predictive analytics
- Proficiency in Python and popular ML libraries
- Proficiency in SQL for complex queries and data transformation
- Experience building REST API-based services
- Experience with modern data and ML technologies such as Docker, Kubernetes, Kafka, Airflow, data warehouses, and data lakes
- Excellent communication skills for presenting findings to technical and non-technical audiences
Nice to have
- Familiarity with dbt for data transformation and testing
- Familiarity with Infrastructure as Code tools like Github Actions and CI/CD pipelines
- Experience working in marketplace or platform contexts where ranking, matching, and pricing impact user experience and business outcomes