data
Posted Apr 8Senior Machine Learning Engineer
at Taskrabbit
San Francisco, United StatesHybrid
Responsibilities
- Model Development & Research: Research, design, and implement machine learning models to solve key business problems in areas like search ranking, recommendations, and content discovery.
- Performance & Quality: 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.
Requirements
- Machine Learning is a cornerstone at Taskrabbit, and we're looking for a seasoned Senior Machine Learning Engineer to join our team and help shape the future of ML/AI at Taskrabbit.
- This is a unique, full-stack role for an individual who is passionate about the entire machine learning lifecycle—from initial research and model development to building the robust infrastructure required to deploy and scale your work.
- As a Senior Machine Learning Engineer, you will tackle exciting challenges that directly impact how people discover and connect with home services on the Taskrabbit platform.
- End-to-End ML Lifecycle: Own the entire lifecycle of ML models, including feature engineering, training, evaluation, deployment, and monitoring.
- Infrastructure & Scalability: 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.
- We welcome applicants from a variety of backgrounds and experiences. Below gives you a sense of how we're thinking about
- BS, MS, or PhD in Computer Science, Statistics, Operations Research, or a related quantitative field.
- experience building and deploying high-quality, production-grade machine learning models and systems.
- 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. •