The Staff Machine Learning Engineer will join the Personalization team at DoorDash, focusing on developing machine learning solutions to enhance the consumer shopping experience in the retail and grocery sectors. This role involves conceptualizing, designing, implementing, and validating algorithmic improvements that drive growth and personalization. The engineer will leverage robust data and machine learning infrastructure to create relevant and seamless user experiences. Collaboration with multi-disciplinary teams and mentoring junior members will also be key aspects of this position.

• 8+ years of industry experience developing machine learning models with business impact and shipping ML solutions to production.
• Proficiency in using AI coding tools in the full software development lifecycle.
• 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, with familiarity in explore/exploit/MAB algorithms and LLMs being a plus.
• Machine learning background in Python, with experience in PyTorch or TensorFlow preferred.
• Ability to communicate technical details to nontechnical stakeholders.
• Desire for impact with a growth-minded and collaborative mindset.

• Develop production machine learning solutions to create a personalized shopping experience.
• Partner with engineering and product leaders to shape the product roadmap using machine learning.
• Mentor junior team members and lead cross-functional pods to create collective impact.