About the Team

The Fraud Machine Learning team builds cutting edge models that play central roles in our important anti-fraud systems. We operate at a massive scale, risking billions of events across 20 countries. We are looking for ML experts who can help us push the technology boundaries and make DoorDash the world’s most safe logistics engine!

About the Role

We’re looking for a passionate Applied Machine Learning engineer to join our team. As a Machine Learning Engineer, you’ll be conceptualizing, designing, implementing, and validating algorithmic solutions to prevent, detect and mitigate fraud. You are excited about opportunities to introduce step function changes to our risking system. You will demonstrate a command of production level machine learning, experience solving end-user problems, and collaborate well with multi-disciplinary teams.

You will report into the engineering manager on our Fraud Machine Learning team in our Operation Excellence organization. Once our offices reopen, we expect this role to be hybrid with some time in-office and some time remote.

You're excited about this opportunity because you will...

• Develop production machine learning solutions to build a safe and frictionless shopping experience for a diverse and expanding retail space. 
• Partner with engineering and product leaders to help shape the product roadmap applying ML
• Mentor junior team members, and lead cross functional pods to create collective impact

You can find out more on our ML blog here

We're excited about you because you have...

• 2 years of industry experience developing machine learning models ( both classical and deep learning) and shipping ML solutions to production.
• Experience with PyTorch or TensorFlow or similar deep learning framework.
• M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Bioinformatics, Economics, or other quantitative fields
• Familiarity with a JVM language (Kotlin/Scala)
• Familiarity with multi-task learning, LLMs and anomaly detection
• Fraud domain knowledge

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

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