DoorDash
Circuit mix
Where DoorDash shows up, by circuit. Each event counts once: 2 if it sponsored, 1 if it only had speakers. Hover a segment for the conference.
- Software engineering & trading tech23%5 events
- Modern data stack & practitioner18%4 events
- AI engineering & MLOps18%3 events
- Open-source data infrastructure9%2 events
- Cloud providers9%2 events
- Python & R data science9%1 event
- Streaming5%1 event
- Postgres & open-source databases5%1 event
- Enterprise, analyst & AI expos5%1 event
Presence by conference and year
Each cell is one conference in one year. Fill shows the company sponsored, shaded by its best tier that year; a dot means it had speakers there. Hover for details; click to open the event.
- Title
- Platinum
- Gold
- Silver
- Bronze
- Other / unlabeled tier
- Had speakers
Activity by year
Three measures on one year axis; each panel has its own scale. 2027, 2028 is still mostly ahead, so its bars are faded and incomplete.
Conferences present at
Distinct conferences each year, split by whether the company sponsored or only had speakers there.
- Sponsored
- Speakers only
Distinct speakers
People from this company on a program that year, each counted once.
Sponsorships by tier
Sponsorship rows per year (one per event and listing), stacked by normalized tier.
- Gold
- Other / unlabeled
Where they've grown or pulled back
FlatSponsored 1 conference in 2026, flat from 1 in 2019.
Counted per conference. 2026 is the latest year whose conferences have mostly happened. Tiers use the best tier each year; swatches show the path, oldest first. A conference counts as pulled out only when a later event published a complete sponsor list, since most events don’t say whether their list is complete.
New 1
First sponsored in 2025 or later.
- AI Engineer (World's Fair, Summit and regional editions)first sponsored 2026, unranked tier
Once or on and off 1
No clear direction, or a gap we can’t confirm because later sponsor lists are incomplete.
- PyCon (national Python conferences)once, 2019, Gold
Lookalikes
Companies with the most similar conference footprint: they sponsor and speak at the same conferences. Bars are cosine similarity, from 0 (nothing shared) to 1 (identical).
1 Cluster: AI Engineer · MLOps World circuit →
Often sponsors alongside
Companies that sponsored the same events, by number of shared events (out of 2 this company sponsored).
| Company | Shared events | Share |
|---|---|---|
| Amazon Web Services | 2 | 100% |
| Bloomberg | 2 | 100% |
| Datadog | 2 | 100% |
| Elastic | 2 | 100% |
| 2 | 100% | |
| Indeed | 2 | 100% |
| 2 | 100% | |
| Microsoft | 2 | 100% |
| Red Hat | 2 | 100% |
| Sentry | 2 | 100% |
| Twilio Segment | 2 | 100% |
| Two Sigma | 2 | 100% |
| 1Password | 1 | 50% |
| Accenture | 1 | 50% |
| Acrew Capital | 1 | 50% |
Neighborhood: companies with nearby conference footprints
DoorDash (ringed) and the 30 companies closest to it on the company map. Close together means they sponsor and speak at many of the same conferences. Distances are only meaningful locally; the axes have no meaning. Dot size: conferences present at. Color: cluster.
Sponsorships 2
| Event | Date | Place | Tier as listed | Normalized tier |
|---|---|---|---|---|
| AI Engineer World's Fair 2026 | Jun 29, 2026 – Jul 2, 2026 | San Francisco, United States | Supporting Partners | Other |
| PyCon US 2019 | May 1–9, 2019 | Cleveland, United States | Gold | Gold |
Speakers 42
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Fabio Flores | QCon AI New York 2026 | speaker | From Signal To Impact: The Eval Loop Behind Doordash’s Agentic Ordering System | — |
| Raghav Saboo | QCon AI New York 2026 | speaker | The New Architecture for Generative Search and Recommendations | — |
| Sudeep Das | Data Outpost 2026 | panelist | AI at Scale Inside Real Companies | — |
| Harsha Reddy | dbt Summit 2026 | speaker | From prototype to production: how DoorDash built a scalable analytics SDLC with dbt and ThoughtSpot | Video |
| Nachiket Paranjape | AI Engineer World's Fair 2026 | speaker | AI Evals Platform for Cross-Functional Teams at Scale | Video |
| Raghav Saboo | AI Engineer World's Fair 2026 | speaker | LLM Recsys at DoorDash | — |
| Swaroop Chitlur Haridas | AI Engineer World's Fair 2026 | speaker | AI Evals Platform for Cross-Functional Teams at Scale | Video |
| Bruna Pereira | QCon AI Boston 2026 | speaker | SafeChat: Building AI-Powered Safety Systems at Scale in a Real-Time Marketplace | — |
| Siddharth Kodwani | QCon AI Boston 2026 | speaker | Building GenAI Platform at DoorDash | — |
| Sudeep Das | QCon AI Boston 2026 | speaker | From Models to Agents: Building Context-Aware Consumer AI at Scale at DoorDash | — |
| Swaroop Chitlur | QCon AI Boston 2026 | speaker | Building GenAI Platform at DoorDash | — |
| Sudeep Das | Data Innovation Summit 2026 | featured | — | — |
| Akshat Goel | QCon San Francisco 2025 | speaker | Write-Ahead Intent Log: A Foundation for Efficient CDC at Scale | — |
| Pradeep Muthukrishnan | QCon San Francisco 2025 | speaker | Dynamic Moments: Weaving LLMs into Deep Personalization at DoorDash | — |
| Sudeep Das | QCon San Francisco 2025 | speaker | Dynamic Moments: Weaving LLMs into Deep Personalization at DoorDash | — |
| Vinay Chella | QCon San Francisco 2025 | speaker | Write-Ahead Intent Log: A Foundation for Efficient CDC at Scale | — |
| Alvin Zhang | Airflow Summit 2025 | talk | Scaling and Unifying Multiple Airflow Instances with Orchestration Frederator | Video |
| Chirag Todarka | Airflow Summit 2025 | talk | Scaling and Unifying Multiple Airflow Instances with Orchestration Frederator | Video |
| Vignesh Chadramohan | Data Council 2025 | talk | Internals of SlateDB: An Embedded Key-Value Store Built on Object Storage | — |
| Gaurav Sharma | Iceberg Summit 2025 | speaker | Iceberg with Flink at DoorDash | Video |
| Tristan Culp | Iceberg Summit 2025 | speaker | Iceberg with Flink at DoorDash | Video |
| Chaitanya Hari | AWS re:Invent 2024 | innovation talk | Generative AI in action: From prototype to production | — |
| Chaitanya Hari | AWS re:Invent 2023 | breakout | Transform self-service experiences with AI and Amazon Connect | Video |
| Jeff Yuan | AWS re:Invent 2023 | breakout | From modernization to innovation: The tales of two hospitality leaders | Video |
| Allen Wang | Flink Forward Seattle 2023 | speaker | Building Scalable Data Lakehouse Integrations with Flink | — |
| Allison Cheng | Flink Forward Seattle 2023 | speaker | Building Scalable Data Lakehouse Integrations with Flink | — |
| Basar Hamdi Onat | Flink Forward Seattle 2023 | speaker | Real-Time Metrics Platform leveraging Flink SQL At DoorDash | — |
| Hien Luu | 4th Annual MLOps World Conference & Expo 2023 | speaker | LLMOps: An Emerging Stack to Productionalize LLM Applications | — |
| Dhaval Shah | Ray Summit 2023 | speaker | From Good to Great: Elevating DoorDash Model Training with Ray | — |
| Hien Luu | Ray Summit 2023 | keynote | — | — |
| Kornel Csernai | Ray Summit 2023 | speaker | Modernizing DoorDash Model Serving Platform with Ray Serve | — |
| Siddharth Kodwani | Ray Summit 2023 | speaker | Modernizing DoorDash Model Serving Platform with Ray Serve | — |
| Swaroop Chitlur | Ray Summit 2023 | speaker | From Good to Great: Elevating DoorDash Model Training with Ray | — |
| Chao Chu | QCon New York 2023 | speaker | Building a Large Scale Real-Time Ad Events Processing System | — |
| Hien Luu | QCon New York 2023 | panelist | Panel: Navigating the Future: LLM in Production | — |
| Lin Du | QCon New York 2023 | speaker | How DoorDash Ensures Velocity and Reliability through Policy Automation | — |
| Allen Wang | QCon San Francisco 2022 | speaker | Data Pipeline AMA w/ Sid Anand & Allen Wang | — |
| Allen Wang | QCon San Francisco 2022 | speaker | From Zero to A Hundred Billion: Building Scalable Real Time Event Processing At DoorDash | — |
| Kunal Shah | QCon San Francisco 2022 | speaker | Fabricator: End-to-End Declarative Feature Engineering Platform | — |
| Akshat Nair | Trino Summit 2021 | speaker | How DoorDash processes petabytes of data by utilizing Trino | — |
| Satya Boora | Trino Summit 2021 | speaker | How DoorDash processes petabytes of data by utilizing Trino | — |
| Zohaib Sibte Hassan | Postgres Conference Silicon Valley 2019 | speaker | The NoSQL store everyone ignored | Slides |