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Software Engineer
Machine Learning, Fraud
Posted on 2/1/2022
INACTIVE
Locations
San Francisco, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Requirements
  • B.S., M.S., or PhD. in Computer Science or equivalent
  • Exceptionally strong knowledge of CS fundamental concepts and OOP languages
  • 5+ years of industry experience
  • Experience building machine learning systems in production
  • Experience with real-time technology problems
Responsibilities
  • Formulate innovative approaches to combat fraud and reduce risk with the powers of ML
  • Create new features, train new models, deploy them into production environment
  • Contribute by extending and improving our ML frameworks and platform, creating next-generation capabilities
DoorDash

5,001-10,000 employees

Local food delivery from restaurants
Company Overview
DoorDash is working to empower local communities and in turn, creating new ways for people to earn, work, and thrive. The company operates the largest food delivery platform in the United States.
Benefits
  • Health & Wellness - Premium medical, dental, and vision insurance plans, including fertility coverage. Monthly gym and wellness reimbursement.
  • Compensation - Competitive salary with bi-annual performance reviews. Meaningful equity opportunities - with quarterly vesting.
  • Time When You Need It - Flexible vacation days for salaried employees. Generous vacation and sick days for hourly team members. Paid Parental Leave to support our DoorDash families.
  • Flexible Work Support - At-home office equipment and monthly WiFi support while working from home. Enjoy your favorite lunch on us while working in one of our offices.
Company Core Values
  • We are one team
  • Make room at the table. We’re committed to growing and empowering a more diverse and inclusive community. We believe that true innovation happens when everyone has the tools, resources and opportunity to thrive.
  • Think outside the room. We strive to be as inclusive as possible and consider those who may not be in the room when making decisions.
  • One team, one fight. We’re in this together, and both success and failure are shared. We are intentional about creating a high-accountability, no-blame culture.