Senior Software Engineer, Machine Learning Infrastructure - Generative AI

About the Team

Door Dash is building the world’s most reliable on-demand logistics engine. Behind the scenes, our Machine Learning Platform (MLP) powers critical real-time decision-making for millions of orders each day, supporting business-critical use cases like Groceries, Logistics, Fraud, Search and Personalization.

At Door Dash, our Data Scientists and ML Engineers have the opportunity to dive into a wealth of delivery data to improve company-wide ML workflows such as Search & Recommendations, Catalog building, Fraud intelligence, Chatbot intelligence. You will join a small team to build systems that empower efficient machine learning at scale, especially in the Generative AI area. This is a remote opportunity, with Pacific Time working hours requirement.

• Use your backend, data, and ML infrastructure expertise to help build a high-quality GenAI platform.
• Build scalable, high-performance data and ML pipelines—from retrieval (e.g., RAG) to batch inference that adapt quickly to new technologies.
• Develop an easy-to-use platform that supports fast iteration and deployment of products powered by Generative AI.
• Improve the reliability, scalability, and monitoring of our GenAI infrastructure, including the LLM gateway, fine‑tuning systems, and model serving.
• Collaborate with ML Engineers and Product Engineers to evolve the ML platform as per their use cases.
• Shape the direction of Door Dash’s centralized ML platform that supports all business functions.

• B.S., M.S., or Ph.D. in Computer Science or equivalent
• Strong fundamentals in computer science and Python
• 4+ years of industry experience in software engineering
• Experience building and deploying machine learning systems in production
• Hands‑on ML experience, including developing and testing your own models (even simple ones)
• Experience building infrastructure in cloud environments—especially backend services and data pipelines at scale

• Experience fine‑tuning and serving open‑weight LLMs in production
• Experience building and deploying AI agents in production
• Experience building and deploying MCP servers in production
• Experience in cloud environments like AWS or GCP

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.

In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.

Door Dash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). Door Dash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family‑forming assistance, and a mental health program, among others.

To learn more about our benefits, visit our careers page here.

See below for paid time off details:

• For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.
• For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week ; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week ; about 2.9 hours/month if working 20 hours/week).

The national base pay ranges for this position within the United States, including Illinois and Colorado.

$130,600 — $192,000 USD

$159,800 — $235,000 USD

$193,800 — $285,000 USD

At…