DoorDash USA
Open positions
Staff Software Engineer, Event Streaming Systems
Staff-level individual contributor on DoorDash's Event Streaming Systems team (Storage org), setting multi-year technical direction for the Kafka-based event streaming platform (including diskless, object-store-backed architectures) that moves trillions of events per day across DoorDash, Wolt, and Deliveroo. Hybrid role requiring residence in the New York Metro Area.
Staff Machine Learning Engineer, Personalization
Staff ML engineer on DoorDash's Personalization team designing, implementing, and shipping production machine learning for growth and personalization in grocery/retail consumer search, using causal inference and recommendation systems. Hybrid role in San Francisco; core stack is Python with PyTorch/TensorFlow.
Software Engineer, Backend (All Teams)
Backend engineer at DoorDash (Seattle, hybrid) building and running large-scale services powering its three-sided delivery marketplace — defining backend architecture, migrating from monolith to microservices, and improving performance, reliability, scalability, and security using REST, SQL/NoSQL stores like Postgres and Redis, and AI coding tools.
Senior Software Engineer, Backend (All Teams)
Senior Backend Engineer at DoorDash builds and operates large-scale backend services powering its three-sided delivery marketplace, defines backend architecture for product areas, and helps migrate from a monolith to microservices while improving performance, reliability, and scalability using REST APIs, SQL/NoSQL stores (Postgres, Redis, Elasticsearch, RabbitMQ), and AI coding tools.
Staff Software Engineering, Backend (All Teams)
Staff Backend Engineer at DoorDash building and scaling the large-scale backend systems behind its on-demand delivery marketplace — setting technical direction, leading cross-team initiatives, and moving the monolith to microservices. Stack centers on REST services, SQL/NoSQL stores (Postgres, Redis, Elasticsearch, RabbitMQ) and AI coding tools.
Staff Software Engineer, Machine Learning
Staff ML engineer at DoorDash building production machine learning for the ads platform (budget pacing, automated bidding, audience targeting/embeddings) and the catalog product knowledge graph, owning the full ML lifecycle from training through deployment and experimentation. Stack includes PyTorch, PySpark, and Snowflake; hybrid role in Seattle.
Senior Machine Learning Engineer, Drive
Senior ML Engineer on DoorDash's Drive team, owning machine learning systems end-to-end for delivery/pickup ETA prediction, merchant prep-time estimation, order release optimization, and LLM/VLM-powered delivery quality signals, using Python, PyTorch, Spark and Airflow; based in San Francisco, Sunnyvale, or Seattle.
Senior Software Engineer, Machine Learning
Senior ML engineer on DoorDash's grocery/retail delivery team, building algorithmic and machine learning improvements to the catalog system and product knowledge graph. Owns the full ML lifecycle—training, deployment, experimentation, monitoring—using tools like PyTorch, PySpark, and Snowflake.
Software Engineer, Data Engineering
Build and scale DoorDash's data infrastructure: design large-scale data models, ETL pipelines, and data lake/warehouse architectures powering reporting, product analytics, and financial decision-making. Core stack includes Python/Java, SQL, Spark, Kafka/Flink, Airflow, and Snowflake/Redshift on AWS/GCP.
Software Engineer, Data Platform
Software engineer on DoorDash's Core Data Platform team, building and scaling the frameworks behind its analytical data stack — ingestion, streaming/batch compute, tooling, and data governance — using Spark, Flink, Kafka, Airflow, and lakehouse tech. Requires 2+ years' experience and being based in or relocating to the Bay Area, Seattle, or New York.
Senior Software Engineering, Backend (All Teams)
Senior Backend Engineer at DoorDash's new São Paulo office, working across product and platform teams to build, release, and operate large-scale backend services, help migrate a monolith to microservices, and improve performance, reliability, and scalability, using SQL/NoSQL stores and AI coding tools.
Software Engineer, Backend - Product Engineering (Brazil)
Backend engineer at DoorDash in São Paulo (hybrid) building and operating large-scale services for its three-sided delivery marketplace: defining backend architecture, improving performance and reliability, and helping migrate a monolith to microservices. Works with REST APIs, Postgres, Redis, Elasticsearch, RabbitMQ, and AI coding tools.
Principal Machine Learning Engineer, Ads & Promos Delivery
Principal ML engineer at DoorDash leading the technical direction for AI-first ads ranking and relevance systems — designing sequence models, deep learning, and LLM-powered decisioning for real-time ad selection and personalization. Owns the full model lifecycle from research to production using Python/Java/C++ and frameworks like PyTorch.
Senior Staff Machine Learning Engineer
Senior Staff ML Engineer on DoorDash's Ads & Promos Delivery team, setting technical direction for AI-first ads ranking and relevance systems — applying sequence modeling, deep learning, and LLMs to personalization and query understanding, and owning the full model lifecycle from research through production at marketplace scale.
Senior Staff Machine Learning Engineer, Consumer
Senior staff-level ML engineer at DoorDash who owns the personalization strategy for the entire consumer shopping journey (search, discovery, checkout) and modernizes the recommendation system with AI/LLMs. Day to day: driving technical vision for a 150+ person org, shipping production ML models, and leading architecture across cross-functional teams.
Software Engineer, ML Infrastructure (MDX)
Builds the agentic layer of DoorDash's ML platform — systems where AI agents run modeling experiments and help ML engineers across DoorDash, Wolt, and Deliveroo train, deploy, and debug models. Core work is backend Python and distributed systems plus LLM/agent infrastructure, evaluation, and observability.