Senior Machine Learning Engineer

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! We are not able to provide visa sponsorship (including H-1B, OPT, or other employment-based visas) for this position. Candidates must be legally authorized to work in the United States without employer sponsorship now or in the future.  About the Role 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. You will play a crucial role in advancing our capabilities in areas like search ranking, content discovery, and recommender systems. You will collaborate closely with data scientists and other engineers to design and implement novel algorithms, and you will partner with software engineers to ensure the scalability, reliability, and optimization of our models in production. What You'll Work On: Model Development & Research: Research, design, and implement machine learning models to solve key business problems in areas like search ranking, recommendations, and content discovery. 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. 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. Software Engineering Excellence: Independently solve complex problems, write clean, efficient, and sustainable code, and actively participate in code reviews, documentation, and the full software engineering lifecycle. Your Areas of Expertise: We welcome applicants from a variety of backgrounds and experiences. Below gives you a sense of how we're thinking about what you'll need to be successful in the role. BS, MS, or PhD in Computer Science, Statistics, Operations Research, or a related quantitative field. 5+ 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 dbt (Data Build Tool) is a plus for transforming and testing data. Familiarity with tools for Infrastructure as Code, such as Terraform, and CI/CD pipelines. 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. Compensation & Benefits:  At Taskrabbit, our approach to compensation is designed to be competitive, transparent, and equitable. Total compensation consists of base pay + bonus + benefits + perks. The base pay range for this position is $150,000 - $200,000. This range is representative of base pay only, and does not include any other total cash compensation amounts, such as company bonus or benefits. Final offer amounts may vary from the amounts listed above and will be determined by factors including, but not limited to, relevant experience, qualifications, geography, and level. You’ll love working here because: Taskrabbit is a Hybrid Company. We value flexibility and choice but also stay committed to regular in-person connection. The People. You will be surrounded by some of the most talented, supportive, smart, and kind leaders and teams -- people you can be proud to work with! The Diverse Culture. We believe that we make better decisions when our workforce reflects the diversity of the communities in which we operate. Women make up half of our leadership team and our diversity representation is a