Principal Machine Learning Engineer, Ads & Promos Delivery

The role

You will lead the technical direction for AI-first ranking and relevance systems for ads and promotions. You will design and build next-generation AI systems using techniques like deep learning and large language models. Your work involves managing the full model lifecycle from research to production.

What you will do

• Apply state-of-the-art machine learning and LLM techniques to personalization, query understanding, and user and content understanding.
• Evaluate ML and LLM models using offline analysis and online experimentation.
• Own the full model lifecycle from research to production.
• Partner with product managers, data scientists, and designers.
• Assess emerging research and translate it into scalable, production-ready systems.
• Build and improve models that impact top and bottom line financials.
• Collaborate cross-functionally with engineering, analytics, product, and operations.
• Set long-term technical vision and drive cross-team alignment.

Required qualifications

• 5+ years of experience building, deploying, and scaling ML and AI models for large-scale, user-facing or data-intensive products.
• Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle.
• BS, MS, or PhD in Computer Science, Engineering, or a related field, or equivalent practical experience.
• Deep expertise in one or more: deep learning, large language models, information retrieval, ranking and relevance, recommendation systems, natural language processing, or content understanding.
• Strong programming skills in Python, Java, or C++.
• Hands-on experience using ML frameworks such as PyTorch, TensorFlow, or XGBoost.
• Extensive experience across the full ML lifecycle including data analysis, feature engineering, model development, evaluation, and monitoring.
• Strong collaborator and communicator.

Nice to have

• Experience designing and deploying LLM-based systems, including prompt engineering and retrieval-augmented generation (RAG) architectures, Generative RecSys.
• Experience solving large-scale, user-centric and content-centric personalization problems, including user modeling, retrieval, ranking, and relevance.
• Demonstrated contributions to the ML community through open-source projects, publications, or applied research in areas like ML, NLP, or information retrieval.

Benefits

• 401(k) plan with employer matching
• 16 weeks of paid parental leave
• Wellness benefits
• Commuter benefits match
• Paid time off
• Paid sick leave
• Medical, dental, and vision benefits
• 11 paid holidays
• Disability and basic life insurance
• Family-forming assistance
• Mental health program

About the company

DoorDash is a technology and logistics company that started by enabling door-to-door delivery. The company is expanding into 40+ global markets and new verticals such as Grocery and Retail.