Taskrabbit is looking for a Senior Machine Learning Engineer to help shape the future of ML/AI at Taskrabbit by tackling challenges that directly impact how people discover and connect with home services on the platform, advancing capabilities in search ranking, content discovery, and recommender systems.
Requirements
- 3+ years of industry experience building and deploying high-quality, production-grade machine learning models and systems.
- Strong theoretical knowledge and hands-on experience in machine learning, particularly in areas like search, ranking, recommender systems, or NLP.
- Solid software engineering skills with proficiency in one or more programming languages, including Python. The candidate should have experience with popular ML libraries like Scikit-learn, lightgbm, xgboost, TensorFlow, PyTorch, etc.
- Proficiency in SQL is also required for writing complex queries and transforming data.
- Experience building REST API-based services.
- Experience with modern data and ML technologies, such as Docker, Kubernetes, Kafka, Airflow, data warehouses (eg snowflake, redshift or BigQuery), and data lakes.
- Familiarity with tools for Infrastructure as Code, such as Terraform, and CI/CD pipelines.
Responsibilities
- Research, design, and implement machine learning models to solve key business problems in areas like search ranking, recommendations, and content discovery.
- Own the entire lifecycle of ML models, including feature engineering, training, evaluation, deployment, and monitoring.
- Build scalable and reliable ML infrastructure and data pipelines that support reproducible feature engineering and machine learning model deployment in real-time, near real-time, and batch processes.
- Build monitoring services to understand data quality and model performance of complex systems, and collaborate with engineering and science teams to optimize existing algorithms for training and evaluation.
- Independently solve complex problems, write clean, efficient, and sustainable code, and actively participate in code reviews, documentation, and the full software engineering lifecycle.
Other
- This role operates on a hybrid schedule requiring two days of in-office collaboration per week.
- The position can be based in either our San Francisco office or our new New York City office (opening January 2026).
- Excellent communication skills, with the ability to present complex findings and recommendations clearly to both technical and non-technical audiences.
- A passion for quickly learning new technologies and a drive to solve challenging problems.
- BS, MS, or PhD in Computer Science, Statistics, Operations Research, or a related quantitative field.
