Staff Machine Learning Engineer - Merchant Tax Categorization Service at DoorDash . This role focuses on building production ML systems to create accurate tax categorization for billions of items across merchants on the DoorDash platform.
Come help us build the world's most reliable on-demand, logistics engine for last-mile retail delivery. We are seeking an experienced machine learning engineer to develop the AI/ML that powers our Merchant solutions.
Were looking for a passionate staff level Applied Machine Learning expert to join our team. In this role, you will utilize our data and ML infrastructure to develop a comprehensive AI/ML service to create accurate tax categorization for billions of restaurants and non-restaurant items at DoorDash. You will lead and build a production-level AI/ML solution, collaborate cross-functionally, push the boundaries of LLM capabilities, and help lead the AI product strategy for the team.
DoorDash empowers local economies by connecting customers with local merchants and Dashers. We are a technology and logistics company committed to helping people get what they want, when they want it, with a focus on growth and well-being for our employees.
Statement of Non-Discrimination: We hire and cultivate diverse teams and do not discriminate or harass based on race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability, veteran status, or other protected characteristics. We encourage applicants from women, non-binary or gender non-conforming, LGBTQIA+, Native American or Alaska Native, Black or African American, Hispanic or Latinx, Native Hawaiian or Other Pacific Islander, differently-abled individuals, caretakers, and parents.
Pursuant to the San Francisco Fair Chance Ordinance, the Los Angeles Fair Chance Initiative for Hiring Ordinance, and any other applicable state or local laws, we consider qualified applicants including those with arrest or conviction records. If you need accommodations, please inform your recruiting contact upon initial connection.
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