# Gary (Bin) Chang

ML engineer on Cognition's SWE-1.5/1.6/1.7 models; now GPU Burner at River AI  
River AI  
San Francisco, California, United States

## At Cognition

- Role: Former ML Engineering (Engineering)
- Joined: Sep 2024
- How they joined: With Windsurf (https://www.autumn.ai/resources/cognition/acquisitions/windsurf)
- Before Windsurf: Member of Technical Staff, Startup Building AI Assistant
- Now: River AI (https://www.linkedin.com/in/changbin)
- Overlapped before Cognition with other Cognition people at: Codeium (Windsurf); Scale AI; Google; Uber (https://www.autumn.ai/resources/cognition/worked-together)

## Identity
- LinkedIn: https://www.linkedin.com/in/changbin
- X: @GoTypescript

## Notes
- Left Cognition after SWE-1.7 (released 2026-07-08; LinkedIn shows Cognition Jul 2025 - Jul 2026) and became "GPU Burner" at River AI from Aug 2026. (https://www.linkedin.com/in/changbin)
- On SWE-1.6 Preview he wrote: "I'm incredibly proud to have contributed to the release of SWE-1-6-preview. While it might be a small step for the industry, it is a massive milestone for Cognition. We are just getting started, and the potential is limitless. Try it out in Windsurf today!" (https://www.linkedin.com/posts/changbin_cognition-an-early-preview-of-swe-16-and-activity-7433998304142647296-tFyC)
- Joined Cognition in July 2025 via the Windsurf acquisition, in his own words: "I joined Cognition last July following the company's acquisition of Windsurf." (https://www.linkedin.com/feed/update/urn:li:activity:7413763117345759232/)
- Listed as an author on Cognition's SWE-1.5 launch post (2025-10-29), byline "By Jacob Teo, Nikhil Jha, Connor Fogarty, Gary Chang ...". (https://cognition.com/blog/swe-1-5)
- On X after the SWE-1.6 GA launch: "SWE-1.6 is the best alternative solution in the market right now,  if you feel the pain the high token cost.

It gets significant boost from SWE 1.5 in terms of problem solving capability and model "user experience",

Please do give it a try." (https://x.com/GoTypescript/status/2041635724974551061)
- Named his Cognition teammates publicly: "I'm now working with a great team, including Silas Alberti, Cheng-Yuan Lee, Ray Wang, Carlo Baronio, Connor Fogarty Ben Pan Emile Timothy Anand and so on...." (https://www.linkedin.com/feed/update/urn:li:activity:7413763117345759232/)
- Joined Codeium/Windsurf in August 2024 (LinkedIn dates ML Engineering at Windsurf Sep 2024 - Jul 2025) and recalled that "Just two months after my start, and prior to the official launch of the Windsurf IDE, the momentum within the internal team's adoption of Windsurf made it very clear that we were on the verge of a breakthrough." (https://www.linkedin.com/feed/update/urn:li:activity:7413763117345759232/)
- River AI was founded by xAI co-founder Igor Babuschkin and raised $1.1B in a round led by General Catalyst, announced 2026-08-11, the same month Chang joined. (https://techcrunch.com/2026/08/11/general-catalyst-leads-1-1b-round-into-2-month-old-river-ai/)
- His view on Cognition training its own models: "Collectively, these advancements empower startups to move into model training, allowing them to develop and vertically optimize models best suited for their specific product scenarios. Cognition is a leader in this area, and we are just starting." He closed with "and most importantly,  we are hiring. :)" (https://www.linkedin.com/feed/update/urn:li:activity:7413763117345759232/)
- His August 2024 thesis for joining Codeium, which he re-quoted: "I am convinced that the field of software engineering is on the brink of a major transformation over the next 2-5 years. ... Programming languages, with their strict semantics, stand to gain significantly from the recent breakthroughs in large language models (LLMs)." (https://www.linkedin.com/feed/update/urn:li:activity:7413763117345759232/)
- At Scale AI (Sep 2020 - Nov 2023), Staff Engineer and Manager who "Led the computer vision (2D) labeling product team", building the web image/video labeling studio, AI pre-labeling, a data collection pipeline "collaborating with Meta Reality Lab", Outlier.ai platform work for GenAI, and a WebGL/PixiJS image segmentation overhaul. (https://www.linkedin.com/in/changbin)
- Open source: his LinkedIn credits him with developing "the open-source PSP integration framework, Sleet" at Bolt (github.com/BoltApp/sleet, a Go library for payment providers such as Adyen, Braintree, Authorize.Net, CyberSource). (https://www.linkedin.com/in/changbin)
- At Uber Freight (Aug 2016 - Feb 2019) he was "the first engineer on the Uber Freight team" and built the MVP from scratch: freight backend, carrier/shipper web apps, driver mobile app, back-office portal, and the load search and recommendation engine. (https://www.linkedin.com/in/changbin)
- On X the day SWE-1.6 GA shipped: "this chart is amazing beautiful,  and it shows that with proper recipe we could improve model capability while keeping the model efficient." (https://x.com/GoTypescript/status/2041635031484133876)
- Promoted Devin publicly: "Try out the new version of Devin,  faster and fully remote and async," (https://x.com/GoTypescript/status/2026352575919141188)
- Before Windsurf (Jan-Sep 2024) he was Member of Technical Staff at a startup building an AI assistant, where he built the "teaching mode" with a "large action model" agent that breaks tasks into steps and learns workflows by observing people in a web browser, plus a GeoLocation platform. (https://www.linkedin.com/in/changbin)
- At Bolt (Apr 2019 - Oct 2020), Manager and Staff Software Engineer who "Led Bolt's financial product team", building the credit card payment gateway engine with Stripe, PayPal, Afterpay and Affirm integrations and a PCI-compliant card data vault; he doubled the team in a year. (https://www.linkedin.com/in/changbin)
- On Uber's Marketplace Platform Team (Dec 2014 - Aug 2016) he ran one of the largest Node.js worker clusters, initiated the move to Go, built redundancy across four data centers, and resolved traffic restriction issues for Uber in China. (https://www.linkedin.com/in/changbin)
- At Google (May 2009 - Nov 2014) he built two generations of Google Social Content Storage (Bigtable for Google Reader, Buzz and Google+ posts; MegaStore for Google+ and Hangouts) and the Google+ fan-in/fan-out dispatch engine. (https://www.linkedin.com/in/changbin)
- Public headline says "GPU Burner at River AI". (https://www.linkedin.com/in/changbin)
- Posts frequent model-internals commentary: on 2025-12-15 he noticed Qwen silently changed Qwen3-Coder-30B-A3B-Instruct intermediate_size "from 5472 to 6144" (a ~12% weight increase); on 2026-01-14 he analysed DeepSeek Math-V2, mHC and Engram papers. (https://www.linkedin.com/posts/changbin_weekend-fun-facts-qwen-updated-its-model-activity-7406143305673015297-D2Qy)
- In April 2025, while at Windsurf, he posted about a corner case in the first entry of the nvidia/OpenMathInstruct-2 training dataset. (https://www.linkedin.com/posts/changbin_weekend-random-posting-ran-into-a-pretty-activity-7319898335132151808-5Nwv)
- Seasoned Engineers, Builder; this comes from the profile summary and preserves the person's own positioning. (https://www.linkedin.com/in/changbin)
- Education: Bachelor in the "Fundamental Science Class" and Master in Computer Science and Technology at Tsinghua University, then PhD Candidate in Computer Science at Vanderbilt University. (https://www.linkedin.com/in/changbin)
- Recent X posts (Oct 2026) on agentic coding languages: "There should be a leaderboard of best coding languages for AI Coding.  Rust so far leads on this, but just by luck." (https://x.com/GoTypescript/status/2106444310879359434)
- Started at YouTube (2008-2009) on the mobile web team, building the smartphone site and an AJAX framework on a customized Google Closure library. (https://www.linkedin.com/in/changbin)
- Previous roles include ML Engineering at Cognition; ML Engineering at Windsurf; Member of Technical Staff at Startup Building AI Assistant; Staff Engineer and Manager at Scale AI; Manager and Staff Software Engineer at Bolt; Senior Staff Engineer, Tech Lead at Uber; Staff Software Engineer at Uber; Senior Software Engineer at Google. (https://www.linkedin.com/in/changbin)
- Education history includes PhD Candidate, Computer Science, Vanderbilt University; Master, Computer Science and Technology, Tsinghua University; Bachelor, Fundamental Science Class, Tsinghua University. (https://www.linkedin.com/in/changbin)
- Location is San Francisco, California, United States. (https://www.linkedin.com/in/changbin)

## Experience
- GPU Burner at River AI - Palo Alto, California, United States (Aug 2026 - Present)
- ML Engineering at Cognition (Jul 2025 - Jul 2026)
- ML Engineering at Windsurf - Mountain View, California, United States (Sep 2024 - Jul 2025)
- Member of Technical Staff at Startup Building AI Assistant - San Francisco Bay Area (Jan 2024 - Sep 2024): Developed the teaching mode, which consists of two main components:
1. A smart AI agent system, known as the large action model, that breaks down complex tasks into multiple steps and utilizes advanced AI models to execute each step efficiently.
2. A workflow designed to learn solutions for complex tasks by observing and analyzing how people complete these tasks through a series of actions in a web browser.

GeoLocation Platform:   Designed and developed a comprehensive GeoLocation platform supporting GPS, cell tower data, and IP-based geolocation. Integrated geocoding and reverse geocoding vendors, providing APIs for feature teams to create location-aware assistant experiences.

Observability Platform:  Spearheaded the creation of an observability platform by researching and selecting the optimal vendor. Implemented log and metric system integrations, rewrote the logging library, and migrated the existing codebase. This initiative established a robust foundation for long-term DevOps operations and significantly enhanced bug triage efficiency.
- Staff Engineer and Manager at Scale AI - San Francisco Bay Area (Sep 2020 - Nov 2023): Led the computer vision (2D) labeling product team, developing Scale's web-based image/video labeling studio. Managed the product and engineering roadmap to align with key metrics.

Built a high-energy engineering team that drove rapid business growth and emphasized quality software development.

Key Projects:
AI Assistant Labeling: Integrated AI pre-labeling into the data workflow.
Data Collection Pipeline: Developed a pipeline from scratch, securing major clients and collaborating with Meta Reality Lab.
Outlier.ai Development: Enhanced platform for multi-domain usage, supporting GenAI growth.
Image Segmentation Overhaul: Improved product with WebGL and PixiJS, boosting resolution capacity and UX speed.
Compensation Platform Extension: Expanded platform for GenAI workloads with new features like direct deposit and tax form generation.
- Manager and Staff Software Engineer at Bolt - San Francisco Bay Area (Apr 2019 - Oct 2020): Led Bolt's financial product team, building the core engine for its independent credit card payment gateway and integrating major solutions like Stripe, PayPal, Afterpay, and Affirm. Developed the open-source PSP integration framework, Sleet, enhancing Bolt's position as a one-stop solution for payment integrations. Spearheaded the creation of Bolt’s PCI-compliant credit card data vault, optimizing processing costs and user experience.

Recruited top talent, doubling the engineering team size in a year. Fostered a collaborative and inclusive environment, mentoring junior engineers and supporting their career growth. Established a long-term architectural vision to scale services and improve code quality continuously.
- Senior Staff Engineer, Tech Lead at Uber - San Francisco Bay Area (Aug 2016 - Feb 2019): As the first engineer on the Uber Freight team, I developed the Minimum Viable Product (MVP) from scratch. This included creating the core backend infrastructure supporting freight business logic and building user-facing platforms: web-based interfaces for carriers and shippers, a mobile app for drivers, and an internal web portal for back-office operations.

I also engineered the load search and recommendation engine, which utilized both rule-based guidelines and machine learning approaches to optimize freight matching. My work laid a strong technical foundation that contributed to Uber Freight's success in the logistics industry.
- Staff Software Engineer at Uber - San Francisco Bay Area (Dec 2014 - Aug 2016): As part of Uber's Marketplace Platform Team, I managed one of the largest Node.js worker clusters globally and initiated the transition to Go, scaling the backend to support rapid business expansion.

 I led the design and implementation of a redundancy and isolation solution across four data centers with seven deployments each, achieving zero global outages. 

As a key contributor to the platform's re-architecture, I successfully led the migration to a new platform. Additionally, I resolved traffic restriction issues for Uber in China and developed a deep understanding of geolocation-related business logic, enhancing the platform's reliability and scalability.
- Senior Software Engineer at Google - Mountain View (May 2009 - Nov 2014): Developed and maintained two generations of Google Social Content Storage systems. The first generation, powered by Bigtable, supported key products such as Google Reader, Gmail Buzz, and Google Plus posts/comments. Transitioned to the second generation using MegaStore, which served as the core backend for Google Plus, Google Hangouts, and other social applications. 

Additionally, engineered Google Plus's dispatch engine, implementing a hybrid fan-in and fan-out strategy to efficiently manage content distribution. This approach ensured scalability to accommodate high-profile users with extensive followings, such as Justin Bieber and Lady Gaga.
- Software Engineer at YouTube (Jan 2008 - Jan 2009): As a member of YouTube's mobile web team, I played a pivotal role in building and maintaining the mobile website, optimizing it for smartphones such as iPhone and Android, as well as high-end feature phones like Nokia, Samsung, and BlackBerry. I developed the site to support hundreds of feature phones, ensuring broad accessibility. 

Additionally, I designed and developed an AJAX framework specifically for the smartphone site, heavily customizing the Google Closure library to enhance performance on smartphone browsers.

## Education
- Vanderbilt University - PhD Candidate, Computer Science
- Tsinghua University - Master, Computer Science and Technology
- Tsinghua University - Bachelor, Fundamental Science Class

## Sources
- https://www.linkedin.com/in/changbin
- https://www.linkedin.com/feed/update/urn:li:activity:7413763117345759232/
- https://cognition.com/blog/swe-1-5
- https://techcrunch.com/2026/08/11/general-catalyst-leads-1-1b-round-into-2-month-old-river-ai/
- https://x.com/GoTypescript
- https://www.linkedin.com/in/changbin?miniProfileUrn=urn%3Ali%3Afsd_profile%3AACoAAAO5aOgBpsSrD0Da6QCmY1flG6U5AbGSHdg
- https://www.linkedin.com/posts/changbin_cognition-an-early-preview-of-swe-16-and-activity-7433998304142647296-tFyC
- https://x.com/GoTypescript/status/2041635724974551061
- https://x.com/GoTypescript/status/2041635031484133876
- https://x.com/GoTypescript/status/2026352575919141188
- https://www.linkedin.com/posts/changbin_weekend-fun-facts-qwen-updated-its-model-activity-7406143305673015297-D2Qy
- https://www.linkedin.com/posts/changbin_weekend-random-posting-ran-into-a-pretty-activity-7319898335132151808-5Nwv
- https://x.com/GoTypescript/status/2106444310879359434


Researched with Autumn (https://www.autumn.ai) from public sources. Updated 2026-11-04. Profile: https://www.autumn.ai/resources/cognition/people/gary-chang · Everyone at Cognition: https://www.autumn.ai/resources/cognition/people