Software Engineer, Machine Learning - Credit & Refund Optimization

DoorDash DoorDash · Consumer · San Francisco, CA · 341 Executive Engineering

Software Engineer, Machine Learning role focused on building and deploying ML systems for credit and refund optimization, personalizing decisions to balance customer experience and operational costs using causal inference and optimization algorithms.

What you'd actually do

  1. Designing and deploying causal inference models to accurately assess the impact of refunds and credits on customer satisfaction, retention, and behavior
  2. Developing optimization frameworks that balance customer experience with operational cost, under policy and budget constraints
  3. Building personalized decision systems that adapt to customer preferences and platform dynamics in real time
  4. Collaborating with engineering, product, and data science partners to shape the roadmap for trust, service recovery, and consumer experience
  5. Leading end-to-end model development, including experimentation, deployment, monitoring, and iteration

Skills

Required

  • Python
  • PyTorch
  • Spark
  • MLflow
  • statistical modeling
  • causal inference
  • optimization algorithms

Nice to have

  • M.S. or Ph.D. in a quantitative field
  • product sense
  • cross-functional leadership

What the JD emphasized

  • delivering machine learning systems with clear business impact
  • personalization
  • optimization
  • causal inference

Other signals

  • personalization
  • optimization
  • causal inference
  • decision systems