Vincent Huang

黄陈谆

Developer, Student, Musician

About Me

Hi, I am Vincent Huang, a software engineer at Databricks.

I graduated from McGill University with a Bachelor's degree in Honours Computer Science and a minor in Musical Science & Technology. And I hold a Master's degree from Carnegie Mellon University in Machine Learning and Natural Language Processing. My career started in telemetry infrastructure, where I worked on the nexxt-generation log delivery system at Databricks. I recently transitioned to focus on observability products, where I adapted my prior experience to build industry-leading query performance insights that scale with second-level latency.

My interests lie in observability products and infrastructure in large-scale distributed systems. And I am also an avid classical guitar hobbyist.

Databricks

Software Engineer IV (2025-11 ~ Present)

- Working on industry-leading products that improve Spark query observability and surface user-facing performance insights.

Software Engineer (2024-03 ~ 2025-11)

- Built the next-generation log delivery infrastructure from the ground up, which increased the data completeness from 99.9% to 99.999%.

Apple

Software Engineer Intern (2023-05 ~ 2023-08)

I joined as the first machine learning engineer on the team.

Major highlights of this internship:

- Service Facade: Lead the end-to-end development of a proxy layer with Spring WebFlux from scratch used by 4 teams while providing advanced customizable features (Rate Limiter, Circuit Breaker) for each of the upstream service.

- VoIP QoE: Research, design, and integrate Quality of Experience(QoE) metrics for call sessions with Machine Learning into Apple’s Retail Platform.

- Deployment and Monitoring: Integrate the application into Kubernetes cluster, set up ACL and security groups. Set up Splunk Stats Services with application.

Unity Technologies

Research Intern (2022-05 ~ 2022-08)

I worked with the Deeppose team in the Unity Labs to help address the pose estimation problem from inverse kinematics using the ProtoRes Network.

Major highlights of this internship:

- Knowledge Distillation and Model Architecture: Designed model architecture which, combined with knowledge distillation, achieving comparable performance to the original model proposed by Harvey et al with only 1/20 of size

- FPS Improvements: Supported 5 times as many frames a second as the original model by improving model inference time

- ML Engineering: Adapted Knowledge Distillation algorithm to motion synthesis tasks

Unity Technologies

Software Developer Intern (2021-05 ~ 2021-08)

I worked with a team of 5 to build and improve the Unity Package Manager

Major highlights of this internship:

- Provided user-facing, event-oriented download progression report for Unity packages

- Unified installing and caching pipeline for packages from different sources

- Established decentralized testing framework for the whole team while maintaining 100% code coverage

- Improved search reply query, which cut the client-side package search time