Staff Software Engineer, Machine Learning - Personalization

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

Staff Software Engineer, Machine Learning - Personalization at DoorDash. Develops production ML solutions for personalized shopping experiences in retail and grocery delivery. Focuses on Causal Inference and Recommendation Systems, with potential familiarity with MAB algorithms and LLMs. Ships ML solutions to production and partners with product leaders.

What you'd actually do

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

Skills

Required

  • 8+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production.
  • M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field
  • Expertise in applied ML for Causal Inference and Recommendation Systems - both classical and deep learning based.
  • Machine learning background in Python
  • Ability to communicate technical details to nontechnical stakeholders

Nice to have

  • Additional familiarity with explore/exploit/MAB algorithms & LLMs is a plus.
  • experience with PyTorch or TensorFlow preferred.

What the JD emphasized

  • 8+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production.
  • Expertise in applied ML for Causal Inference and Recommendation Systems

Other signals

  • develop production machine learning solutions
  • shipping ML solutions to production
  • applied ML for Causal Inference and Recommendation Systems