Companies
Lyft
Product category: ML platforms 56% confident
Org type: End-user enterprise 99% confident
Also listed as 4 other names
Lyft Inc · Lyft Level 5 · Lyft, Inc · lyft
Conferences sponsored7
Events sponsored7
Speaker slots6041 distinct people
Conferences present at21sponsor or speaker
Years active2019–2026
Talks, past 12 months4#552 on the communication index · many voicesCircuit mix
Where Lyft shows up, by circuit. Each event counts once: 2 if it sponsored, 1 if it only had speakers. Hover a segment for the conference.
- Streaming27%11 events
- Research17%4 events
- Modern data stack & practitioner15%6 events
- Python & R data science10%5 events
- Open-source data infrastructure8%4 events
- Cloud providers6%3 events
- AI engineering & MLOps6%3 events
- Software engineering6%3 events
- Vendor flagships & roadshows4%2 events
The year around now
Conferences where Lyft sponsored or had speakers in the past 12 months, and the announced events it is already listed for. One row per conference, January to December; hover a mark for the event and the company's role.
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.
Conferences present at
Distinct conferences each year, split by whether the company sponsored or only had speakers there.
- Sponsored
- Speakers only
11
6
1
8
3
2
3
3
Distinct speakers
People from this company on a program that year, each counted once.
16
10
10
7
2
3
2
Sponsorships by tier
Sponsorship rows per year (one per event and listing), stacked by normalized tier.
- Title
- Platinum
- Gold
- Silver
- Other / unlabeled
6
1
Where they've grown or pulled back
DownNothing recorded in 2026; sponsored 1 conference in 2021.
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.
Pulled out 3
Not sponsored since 2024 or earlier, though a later event published a complete sponsor list without them.
- AI By the Baylast sponsored 2021; the conference ran again in 2023 and 2025
- CVPR (IEEE/CVF Conference on Computer Vision and Pattern Recognition)last sponsored 2019; the conference ran again in 2022–26
- ICML (International Conference on Machine Learning)last sponsored 2019; the conference ran again in 2022–26
Once or on and off 4
No clear direction, or a gap we can’t confirm because later sponsor lists are incomplete.
- ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)once, 2019, Silver
- Current (formerly Kafka Summit)once, 2019, Silver
- Flink Forwardonce, 2019, Gold
- NeurIPS (Conference on Neural Information Processing Systems)once, 2019, Title
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).
8 Cluster: NeurIPS · ICML circuit →
Often sponsors alongside
Companies that sponsored the same events, by number of shared events (out of 7 this company sponsored).
| Company | Shared events | Share |
|---|---|---|
| Amazon Web Services | 5 | 71% |
| Apple | 5 | 71% |
| 5 | 71% | |
| IBM | 5 | 71% |
| Microsoft | 5 | 71% |
| Alibaba Cloud | 4 | 57% |
| Inspur | 4 | 57% |
| NAVER | 4 | 57% |
| Tencent | 4 | 57% |
| Baidu | 3 | 43% |
| Bloomberg | 3 | 43% |
| Bosch | 3 | 43% |
| ByteDance | 3 | 43% |
| The D. E. Shaw Group | 3 | 43% |
| DiDi | 3 | 43% |
Neighborhood: companies with nearby conference footprints
Lyft (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 7
| Event | Date | Place | Tier as listed | Normalized tier |
|---|---|---|---|---|
| Scale By the Bay 2021 | Oct 27–29, 2021 | — | Friend | Other |
| NeurIPS 2019 | Dec 8–14, 2019 | Vancouver, Canada | Diamond | Title |
| Kafka Summit San Francisco 2019 | Sep 30, 2019 – Oct 1, 2019 | San Francisco, United States | Silver | Silver |
| KDD 2019 (25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining) | Aug 4–8, 2019 | Anchorage, United States | Silver | Silver |
| CVPR 2019 | Jun 16–20, 2019 | Long Beach, United States | Platinum | Platinum |
| ICML 2019 | Jun 9–15, 2019 | Long Beach, United States | Silver | Silver |
| Flink Forward San Francisco 2019 | Apr 1–2, 2019 | San Francisco, United States | Gold Sponsor | Gold |
Speakers 60
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Ken Obata | Airflow Summit 2026 | talk | Self-Service DAGs: Event-Driven Design for GitHub Actions and Airflow at Lyft | Slides · Video |
| Ken Obata | PyData London 2026 | talk | Beyond Spark MLlib: Deduplicating Common Crawl at Scale | — |
| Tao Ye | GTC 2026 | featured | — | — |
| Jason Vogrinec | AWS re:Invent 2025 | innovation talk | Build and scale AI: from reliable agents to transformative systems | Video |
| Rakesh Kumar | Beam Summit 2025 | speaker | Scaling Real-Time Feature Generation Platform @Lyft | Slides · Video |
| Jeana Choi | Open House 2025 (San Francisco) | speaker | — | — |
| Konstantin Gizdarski | 5th Annual MLOps World and Generative AI World Conference 2024 | speaker | Generative AI Infrastructure at Lyft | — |
| Ravi Magham | Beam Summit 2024 | speaker | Realtime Forecasting using Beam | Slides · Video |
| Charles Song | Trino Summit 2023 | speaker | Transitioning to Trino: Evaluating Lyft's query engine capabilities | Slides · Video |
| Konstantin Gizdarski | Flink Forward Seattle 2023 | speaker | Real-Time Machine Learning at Scale with Flink at Lyft | — |
| Seth Saperstein | Flink Forward Seattle 2023 | speaker | Real-Time Machine Learning at Scale with Flink at Lyft | — |
| Anindya Saha | PyData Seattle 2023 | tutorial | Being well informed: Building a ML Model Observability pipeline | Video |
| Han Wang | PyData Seattle 2023 | speaker | How to incrementally scale existing workflows on Spark, Dask or Ray? | Video |
| Jun Liu | PyData Seattle 2023 | speaker | How to incrementally scale existing workflows on Spark, Dask or Ray? | Video |
| Rajeev Prabhakar | PyData Seattle 2023 | tutorial | Being well informed: Building a ML Model Observability pipeline | Video |
| Charles Song | Trino Summit 2022 | speaker | Trino for Large Scale ETL at Lyft | Slides · Video |
| Ritesh Varyani | Trino Summit 2022 | speaker | Trino for Large Scale ETL at Lyft | Slides · Video |
| Han Wang | PyData NYC 2022 | speaker | Testing Big Data Applications (Spark, Dask, and Ray) | Video |
| Tom Wanielista | QCon San Francisco 2022 | speaker | Adopting Continuous Deployment at Lyft | — |
| Tom Wanielista | QCon San Francisco 2022 | speaker | Enabling Change @ Scale Roundtable | — |
| Anindya Saha | Ray Summit 2022 | speaker | Distributed training with Ray on Kubernetes | — |
| Han Wang | Ray Summit 2022 | speaker | Distributed training with Ray on Kubernetes | — |
| Shaswat Shah | SciPy 2022 | speaker | Comparing the Different Ways to Scale Python and Pandas Code | — |
| Mihir Mathur | 3rd Annual MLOps World 2022 | workshop | Defending Against Decision Degradation with Full-Spectrum Model Monitoring : Case Study and AMA | — |
| Max Payton | Airflow Summit 2022 | talk | Kyte: Scalable and Isolated DAG Development Experience at Lyft | Slides · Video |
| Paul Dittamo | Airflow Summit 2022 | talk | Kyte: Scalable and Isolated DAG Development Experience at Lyft | Slides · Video |
| Han Wang | PyCon US 2022 | speaker | Comparing the Different Ways to Scale Python and Pandas Code | Video |
| Jake Kaufman | QCon London 2022 | speaker | Developer Enablement - What's Next? | — |
| Jake Kaufman | QCon London 2022 | speaker | Breaking up Lyft’s Development Monolith | — |
| Alex Bain | AWS re:Invent 2020 | breakout | Accelerating autonomous vehicle solutions with SageMaker, featuring Lyft | Slides · Video |
| Lakshmi Rao | Flink Forward Global 2020 | speaker | Zero-downtime upgrades of Flink applications | — |
| Maximilian Michels | Beam Digital Summit 2020 | keynote | Keynote: The state of Apache Beam | Video |
| Maximilian Michels | Beam Digital Summit 2020 | speaker | Office hours: Java SDK, Go, Spark, Flink | — |
| Maximilian Michels | Beam Digital Summit 2020 | speaker | Closing remarks and giveaways | — |
| Maximilian Michels | Beam Digital Summit 2020 | speaker | From pipeline to execution: What happens when you run() your pipeline? | Video |
| Haytham Abuelfutuh | Data Council SF 2020 (online) | talk | Flyte: Cloud Native Machine Learning & Data Processing Platform | — |
| Tao Feng | Airflow Summit 2020 | keynote | Keynote: How large companies use Airflow for ML and ETL pipelines | Video |
| Kailash Hassan Dayanand | Flink Forward Virtual Conference 2020 | speaker | Large-scale near-real-time (NRT) data analytics platform empowered by Apache Flink | — |
| Micah Wylde | Flink Forward Virtual Conference 2020 | speaker | How Lyft built a streaming data platform with Flink on Kubernetes | — |
| Ying Xu | Flink Forward Virtual Conference 2020 | speaker | Large-scale near-real-time (NRT) data analytics platform empowered by Apache Flink | — |
| Jose Nino | QCon London 2020 | speaker | Next Generation Client APIs in Envoy Mobile | Video |
| Sherin Thomas | QCon London 2020 | speaker | Machine Learning Through Streaming at Lyft | Video |
| Allyson Gale | AWS re:Invent 2019 | breakout | Cloud-native machine learning at Lyft with AWS Batch and Amazon EKS | Slides · Video |
| Darek Grala | AWS re:Invent 2019 | breakout | Optimize your storage performance with Amazon S3, ft. Lyft | Slides · Video |
| Giacomo Dabisias | AWS re:Invent 2019 | breakout | Optimize your storage performance with Amazon S3, ft. Lyft | Slides · Video |
| Henry Yang | AWS re:Invent 2019 | breakout | Supercharge your real-time apps with Amazon ElastiCache | Slides · Video |
| Matthew Smith | AWS re:Invent 2019 | breakout | Cloud-native machine learning at Lyft with AWS Batch and Amazon EKS | Slides · Video |
| Lakshmi Rao | Flink Forward Europe 2019 | speaker | Running Flink in production: The good, the bad and the in-between | — |
| Sherin Thomas | Flink Forward Europe 2019 | speaker | Enabling Machine Learning with Apache Flink | — |
| Micah Wylde | Beam Summit North America 2019 | speaker | Running Apache Flink and Apache Beam on Kubernetes | Video |
| Rakesh Kumar | Beam Summit North America 2019 | speaker | Pricing Lyft rides with Apache Beam - a case study in migrating from a worker-based workflow to streaming | Video |
| Kumar Chellapilla | KDD 2019 (25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining) | ADS invited talk | Building a Better Self-Driving Car: Hardware, Software, and Knowledge | — |
| Puneet Jaiswal | Presto Summit 2019 | speaker | Dynamic Presto Scaling | Slides |
| Sherin Thomas | Beam Summit Europe 2019 | speaker | Machine Learning with Flink and Beam | Video |
| Thomas Weise | Berlin Buzzwords 2019 | talk | Streaming your shared ride | Slides · Video |
| Tao Feng | Data Council San Francisco 2019 | talk | Amundsen: A Data Discovery Platform From Lyft | — |
| Akshay Balwally | Flink Forward San Francisco 2019 | speaker | Streaming your Lyft Ride Prices | — |
| Anand Swaminathan | Flink Forward San Francisco 2019 | speaker | Managing Flink on Kubernetes - FlinkK8sOperator | — |
| Ketan Umare | Flink Forward San Francisco 2019 | speaker | Managing Flink on Kubernetes - FlinkK8sOperator | — |
| Thomas Weise | Flink Forward San Francisco 2019 | speaker | Streaming your Lyft Ride Prices | — |