Base Salary
$243k - $357k/yr
Responsibilities
- Set the long-term technical vision for AI-first ads ranking, relevance, and personalization systems.
- Build and improve large-scale models that select, order, and personalize ads in real time.
- Apply sequence modeling, deep learning, large language models, query understanding, representation learning, contextual relevance, and multi-objective optimization.
- Own the full model lifecycle from research and data analysis through development, evaluation, production deployment, monitoring, and iteration.
- Design offline analyses, online A/B experiments, metrics, and evaluations to measure quality, impact, and tradeoffs.
- Translate emerging machine learning and AI research into scalable production systems operating under strict latency, scale, and reliability constraints.
- Partner with engineering, product, analytics, operations, data science, and design teams to deliver user-facing improvements.
- Drive cross-team alignment while balancing advertiser value, consumer experience, and marketplace health.
Requirements
- At least 5 years of experience building, deploying, and scaling machine learning and AI models for large-scale, user-facing or data-intensive products.
- Bachelor’s, master’s, or PhD in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Proficiency with AI coding tools such as Claude Code, Codex, or Cursor across the software development lifecycle.
- Deep expertise in areas such as 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++, with hands-on experience using PyTorch, TensorFlow, or XGBoost.
- Extensive experience with data analysis, feature engineering, iterative model development, offline and online evaluation, monitoring, and continuous improvement.
- Experience designing and deploying LLM-based systems, prompt engineering, retrieval-augmented generation architectures, or Generative RecSys is preferred.
- Experience with large-scale personalization, user modeling, retrieval, ranking, and relevance is preferred.
- Contributions to the machine learning community through open-source projects, publications, or applied research are preferred.
Benefits
- 401(k) plan with employer matching
- 16 weeks of paid parental leave
- Wellness benefits and expense reimbursement
- Commuter benefits match
- Flexible paid time off/vacation for salaried roles
- 80 hours of paid sick time per year for salaried roles
- Medical, dental, and vision benefits
- 11 paid holidays
- Disability and basic life insurance
- Family-forming assistance
- Mental health program
- Equity grant opportunities
- National base pay range applies to the United States, including Illinois and Colorado
Categories
About DoorDash
At DoorDash, our mission to empower local economies shapes how our team members move quickly and always learn and reiterate to support merchants, Dashers and the communities we serve. We are a technology and logistics company that started with door-to-door delivery, and we are looking for team members who can help us go from a company that is known for delivering food to a company that people turn to for any and all goods. DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. Our leaders seek the truth and welcome big, hairy, audacious questions. We are grounded in our company values, and we make intentional decisions that are both logical and display empathy for our range of users—from Dashers to Merchants to Customers.