databricks > databricks Employee Directory > Mingxuan Chai
mingxuan-chai-076
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Mingxuan Chai's Personal Email and Phone Number
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Mingxuan Chai
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Mingxuan Chai's Current Workplace
DatabricksCompany Size
2500+
Amount Raised
$3.5B
Databricks is the lakehouse company. More than 7,000 organizations worldwide — including Comcast, Condé Nast, H&M, and over 40% of the Fortune 500 — rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world’s toughest problems.\n\n---\nAttention: Databricks applicants\n\nDue to reports of phishing, we’re requesting that all Databricks applicants apply through our official Careers page at databricks.com/company/careers (good news — you are here). All official communication from Databricks will come from email addresses ending with @databricks.com or @goodtime.io (our meeting tool).
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Notable Investors
Microsoft, Andreessen Horowitz, Gaingels, BlackRock, Tiger Global Management
Big Data
Analytics
Cloud Computing
Cloud Data Services
Experience
Databricks
Sep 2022 - Present
Senior Software Engineer
Aug 2024 - Present
• 10 mosSoftware Engineer
Sep 2022 - Aug 2024
• 2 yrsClusters Core Team
VMware
Jul 2019 - Sep 2022
Senior Member Of Technical Staff
Jul 2022 - Sep 2022
• 3 mosMember Of Technical Staff 3
May 2021 - Jul 2022
• 1 yr 3 mosMember Of Technical Staff, Propel
Jul 2019 - May 2021
• 1 yr 11 mosNSX Cloud-native Application Platform
•Prototyped, architected, and built cloud-native Kubernetes-based data-intensive platforms and applications.
•Engaged in all microservices development, design, and decision-making processes as the team tech lead, including service scaling, trust-management, platform API server, monitoring/telemetry, etc.
•Independently led a pre-commit test framework project to create the 1st end-to-end testing framework for the pre-commit stage in NSBU.
•Engaged in all stages of the DevSecOps practices
•Led data pipeline and analytics API performance tuning for all releases
Skills: Apache Spark · Java · MinION Object Storage Suite · Distributed Systems · Helm Charts · Go (Programming Language) · Apache Druid · Apache Kafka · Containerization · Cloud Applications · Microservices · Cloud Security · Kubernetes
Deep Learning Engineer Intern
uSens Inc.
May 2018 - Aug 2018
• 4 mos•Implemented and deployed a real-time multiple gesture detection deep learning model for mobile devices, outperforming competitive products such as Tik Tok and Meitu by 30% shorter inference time; Released corresponding Android application by Java; Built related AI infrastructure including data collection, online annotation and image augmentation.
•Improved current hand pose skeleton estimation deep network with C++ and Python, reducing joints position prediction mean error from 1.6 pixels to 0.6 pixels.
•Developed a dynamic gesture classification model for human vehicle interaction using gestures.
Skills: Deep Learning · Android · Machine Learning
Peking University
Mar 2016 - Jul 2017
Research Assistant
Aug 2015 - Jul 2017
• 2 yrs•Group: NELVT Lab Media Learning Group
•Advisor: Prof. YongHong Tian
•Explored the optimal architectures of a biological neural computing and adaptive visual information processing framework: Human Retina Simulator
•Implemented a project based on Fast-RCNN architecture to fine-tune on PKU Surveillance Dataset (PKU-SVD) truth ground and detect in a test dataset
•Finished thesis on fine-grained classification of pedestrians in video
Research Assistant
Mar 2016 - Jun 2016
• 4 mos•Group: Graphics Group
•Advisor: Prof. Sheng Li
•Learned progressive photon mapping theory and programming with OptiX framework and finished a research project proposing a new photon mapping animation rendering algorithm which was submitted to GRAPP 2017
Research Assistant
University of California San Diego
Jul 2016 - Sep 2016
• 3 mos• Group: Artificial Intelligence Group
• Advisor: Gary Cottrell
• Participated implementation of a neural network for fine-grained classification, based on Recurrent Attention Model, on NABird Dataset
Education
- 2017 - 2019Carnegie Mellon UniversityMaster of Science - MS, Computer Software Engineering
- 2013 - 2017Peking UniversityBachelor's degree, Computer Science