Senior Software Engineer, Machine Learning Infrastructure - Generative AI DoorDash 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 Ads, Groceries, Logistics, Fraud, and Search. About the Role At DoorDash, 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, and 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 hybrid opportunity in San Francisco, with a 3 days/week in-office requirement. You’re excited about this opportunity because you will… Use your backend, data, and ML infrastructure expertise to help build reliable, high-quality products powered by Generative AI. Develop an easy-to-use ML platform that supports fast iteration and deployment of GenAI solutions. Collaborate with Data Scientists, ML Engineers, and Product Engineers to evolve the ML platform as per their use cases. Build scalable, high-performance data and ML pipelines—from retrieval (e.g., RAG) to batch inference—that adapt quickly to new technologies. Shape the direction of DoorDash’s centralized ML platform that supports all business functions. Improve the reliability, scalability, and monitoring of our GenAI infrastructure, including the Gateway, fine-tuning systems, and model serving. We’re excited about you because… B.S., M.S., or PhD. 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 data processing or distributed systems Familiarity with GenAI coding tools like Cursor or Aider Nice To Haves Familiarity with Python ML tools (e.g., Pandas, PyTorch, TensorFlow) Experience with Spark, Databricks, and workflow tools like Airflow or Dagster Comfortable working with large language models (e.g. GPT, Gemini, Llama, Deepseek, Qwen), including fine-tuning and batch inference Experience in cloud environments like AWS or GCP Compensation 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. DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package for all regular employees that includes a 401(k) plan with an employer match, paid time off, paid parental leave, wellness benefits, and several paid holidays. Paid sick leave in compliance with applicable laws (i.e. Colorado Healthy Families and Workplaces Act). Additionally, for full-time employees, DoorDash offers medical, dental, and vision benefits, disability and basic life insurance, family-forming assistance, a commuter benefit match, and a mental health program, among others. The base pay for this position ranges from our lowest geographical market up to our highest geographical market within the United States.
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