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| { | |
| "$schema": "https://raw.githubusercontent.com/jsonresume/resume-schema/v1.0.0/schema.json", | |
| "basics": { | |
| "name": "Junjun Deng", | |
| "label": "Staff Software Engineer | ML Infrastructure & Distributed Systems", | |
| "image": "", | |
| "email": "inivy@msn.com", | |
| "phone": "+8613126496289", | |
| "url": "https://medium.com/@cnjdeng", | |
| "summary": "Staff Software Engineer with 10+ years of experience specializing in ML Infrastructure, distributed systems, and large-scale recommendation systems. Currently leading MLOps initiatives at Tubi, serving 100M+ monthly active users. Expertise in Kubernetes, experimentation platforms, and high-performance backend services.", | |
| "location": { | |
| "countryCode": "CN", | |
| "region": "China" | |
| }, | |
| "profiles": [ | |
| { | |
| "network": "GitHub", | |
| "username": "lilac", | |
| "url": "https://github.com/lilac" | |
| }, | |
| { | |
| "network": "Medium", | |
| "username": "cnjdeng", | |
| "url": "https://medium.com/@cnjdeng" | |
| } | |
| ] | |
| }, | |
| "work": [ | |
| { | |
| "name": "Tubi Inc.", | |
| "position": "Staff Software Engineer", | |
| "url": "https://tubitv.com", | |
| "startDate": "2021-01", | |
| "summary": "Serve as a key member of the ML Infrastructure team at Tubi, a leading US AVOD streaming service with 100M+ monthly active users.", | |
| "highlights": [ | |
| "Architect and maintain critical MLOps services that power Tubi's recommendation system", | |
| "Built online feature store processing 500K+ reads/sec and 1M+ writes/sec", | |
| "Manage personalization orchestrator service coordinating 100+ machine learning models", | |
| "Drive infrastructure improvements directly impacting user engagement and platform scalability" | |
| ] | |
| }, | |
| { | |
| "name": "Alibaba Group", | |
| "position": "Senior Software Engineer", | |
| "url": "https://www.alibaba.com", | |
| "startDate": "2018-11", | |
| "endDate": "2020-12", | |
| "summary": "Led the design and implementation of multiple mission-critical services for UC News, a service integrated with UC Browser serving 100M+ users.", | |
| "highlights": [ | |
| "Designed and implemented mission-critical services for UC News platform", | |
| "Served 100M+ users across multiple regions", | |
| "Built high-performance backend services with focus on scalability and reliability" | |
| ] | |
| }, | |
| { | |
| "name": "Maiduote Ltd", | |
| "position": "Architect & R&D Director", | |
| "startDate": "2017-09", | |
| "endDate": "2018-11", | |
| "summary": "Directed R&D department and established AI department from the ground up.", | |
| "highlights": [ | |
| "Established and led a 5-person AI department from scratch", | |
| "Delivered knowledge graph-based chatbot for healthcare platform", | |
| "Reduced doctor-patient communication time by 60% while maintaining high accuracy", | |
| "Led architectural refactoring of 24haowan.com healthcare platform" | |
| ] | |
| }, | |
| { | |
| "name": "Shuyun E-commerce Ltd", | |
| "position": "Cofounder & Technical Lead", | |
| "startDate": "2016-07", | |
| "endDate": "2017-09", | |
| "summary": "Co-founded and served as Technical Lead for a startup.", | |
| "highlights": [ | |
| "Conceptualized and built SameMo, a smart photo-sharing application with facial recognition", | |
| "Delivered complete solution: back-end infrastructure, iOS and Android apps in 4 months", | |
| "Led product vision and full-stack development from concept to market launch", | |
| "Pioneered innovative photo collection technology in Chinese market" | |
| ] | |
| }, | |
| { | |
| "name": "SafetyCulture Inc.", | |
| "position": "Senior Software Engineer", | |
| "url": "https://safetyculture.com", | |
| "startDate": "2015-01", | |
| "endDate": "2016-06", | |
| "summary": "Developed and maintained Android application for iAuditor, a leading workplace safety inspection platform used by 30K+ organizations worldwide.", | |
| "highlights": [ | |
| "Built key features for iAuditor Android app used by 30K+ organizations", | |
| "Implemented offline data synchronization and report generation", | |
| "Contributed to mobile application serving global enterprise customers" | |
| ] | |
| } | |
| ], | |
| "education": [ | |
| { | |
| "institution": "University of Western Sydney", | |
| "url": "https://www.westernsydney.edu.au", | |
| "area": "Computing and Mathematics", | |
| "studyType": "Master of Science (Honours)", | |
| "startDate": "2012", | |
| "endDate": "2014", | |
| "score": "", | |
| "courses": [ | |
| "Answer Set Programming", | |
| "Artificial Intelligence" | |
| ] | |
| }, | |
| { | |
| "institution": "Sun Yat-sen University", | |
| "url": "https://www.sysu.edu.cn", | |
| "area": "Network Engineering", | |
| "studyType": "Bachelor of Engineering", | |
| "startDate": "2007", | |
| "endDate": "2011", | |
| "score": "3.7/4.0", | |
| "courses": [ | |
| "Distributed Systems", | |
| "Algorithms", | |
| "Network Architecture" | |
| ] | |
| } | |
| ], | |
| "awards": [ | |
| { | |
| "title": "Qatar National Foundation Postgraduate Research Award", | |
| "date": "2012", | |
| "awarder": "University of Western Sydney", | |
| "summary": "Full scholarship for postgraduate research (2012-2014)" | |
| }, | |
| { | |
| "title": "National Endeavor Scholarship", | |
| "date": "2010", | |
| "awarder": "Sun Yat-sen University", | |
| "summary": "Merit-based scholarship for academic excellence" | |
| } | |
| ], | |
| "publications": [ | |
| { | |
| "name": "Answer Set Programming with One Incremental Variable (ivASP)", | |
| "publisher": "Academic Journal", | |
| "releaseDate": "2014", | |
| "summary": "Proposed ivASP as a novel extension to traditional Answer Set Programming. Developed a complete solver implementation and published peer-reviewed research documenting theoretical foundations and practical applications." | |
| } | |
| ], | |
| "skills": [ | |
| { | |
| "name": "ML Infrastructure", | |
| "level": "Expert", | |
| "keywords": [ | |
| "Kubernetes", | |
| "Docker", | |
| "MLOps", | |
| "Model Serving", | |
| "Microservices", | |
| "HPA/VPA" | |
| ] | |
| }, | |
| { | |
| "name": "Experimentation", | |
| "level": "Expert", | |
| "keywords": [ | |
| "A/B Testing", | |
| "Interleaving Experiments", | |
| "Statistical Analysis" | |
| ] | |
| }, | |
| { | |
| "name": "Programming Languages", | |
| "level": "Expert", | |
| "keywords": [ | |
| "Python", | |
| "Java", | |
| "Scala", | |
| "C/C++", | |
| "TypeScript", | |
| "Rust", | |
| "Haskell", | |
| "Go" | |
| ] | |
| }, | |
| { | |
| "name": "Cloud & DevOps", | |
| "level": "Advanced", | |
| "keywords": [ | |
| "AWS", | |
| "GCP", | |
| "Terraform", | |
| "CI/CD", | |
| "Infrastructure-as-Code" | |
| ] | |
| }, | |
| { | |
| "name": "ML & Data", | |
| "level": "Advanced", | |
| "keywords": [ | |
| "TensorFlow", | |
| "Recommendation Systems", | |
| "Distributed Training" | |
| ] | |
| }, | |
| { | |
| "name": "Backend", | |
| "level": "Expert", | |
| "keywords": [ | |
| "MySQL", | |
| "Cassandra", | |
| "PostgreSQL", | |
| "Redis", | |
| "Message Queues" | |
| ] | |
| }, | |
| { | |
| "name": "Systems", | |
| "level": "Expert", | |
| "keywords": [ | |
| "Linux/Unix", | |
| "Distributed Systems", | |
| "Monitoring & Observability" | |
| ] | |
| }, | |
| { | |
| "name": "Web Development", | |
| "level": "Advanced", | |
| "keywords": [ | |
| "React", | |
| "Flask", | |
| "Django", | |
| "REST APIs", | |
| "gRPC" | |
| ] | |
| } | |
| ], | |
| "languages": [ | |
| { | |
| "language": "Chinese", | |
| "fluency": "Native speaker" | |
| }, | |
| { | |
| "language": "English", | |
| "fluency": "Fluent (IELTS 7)" | |
| } | |
| ], | |
| "projects": [ | |
| { | |
| "name": "Accelerating ML Experimentation with Interleaving - 20x Sensitivity Gain", | |
| "startDate": "2025", | |
| "endDate": "2025", | |
| "description": "Led a cross-team initiative to implement interleaving experiments for Tubi's recommendation system, achieving 20x higher sensitivity compared to traditional A/B testing.", | |
| "highlights": [ | |
| "Achieved 20x higher sensitivity compared to traditional A/B testing", | |
| "Enabled direct comparison of ranking algorithms through interleaved result presentation", | |
| "Reduced experiment duration from weeks to days", | |
| "Accelerated ML model iteration velocity across entire ML organization" | |
| ], | |
| "keywords": [ | |
| "Experimentation", | |
| "A/B Testing", | |
| "Interleaving", | |
| "Recommendation Systems", | |
| "ML Infrastructure" | |
| ] | |
| }, | |
| { | |
| "name": "Automated Resource Optimization for Large-Scale ML Model Serving", | |
| "startDate": "2024", | |
| "endDate": "2024", | |
| "description": "Led a cost optimization initiative for Tubi's machine learning infrastructure, managing hundreds of Kubernetes pods serving 100+ models.", | |
| "highlights": [ | |
| "Managed hundreds of Kubernetes pods serving 100+ models across thousands of CPU cores", | |
| "Implemented intelligent orchestration of HPA and VPA", | |
| "Achieved 24% reduction in infrastructure costs (saving $500K+ annually)", | |
| "Maintained service quality while optimizing resource utilization" | |
| ], | |
| "keywords": [ | |
| "Kubernetes", | |
| "Cost Optimization", | |
| "MLOps", | |
| "HPA", | |
| "VPA", | |
| "Resource Management" | |
| ] | |
| }, | |
| { | |
| "name": "SameMo - Smart Photo Sharing Platform", | |
| "startDate": "2016", | |
| "endDate": "2017", | |
| "description": "Developed an innovative mobile application that leverages facial recognition technology to automatically help users discover and collect their photos taken by others.", | |
| "highlights": [ | |
| "Leveraged facial recognition for automatic photo collection", | |
| "Pioneered concept in Chinese market", | |
| "Single-handedly designed complete product experience and full-stack implementation", | |
| "Delivered production-ready back-end, iOS, and Android apps in 4 months" | |
| ], | |
| "keywords": [ | |
| "Mobile Development", | |
| "Facial Recognition", | |
| "iOS", | |
| "Android", | |
| "Product Design" | |
| ] | |
| }, | |
| { | |
| "name": "Android Port of ImageMagick", | |
| "startDate": "2014", | |
| "description": "Successfully ported the renowned cross-platform ImageMagick image processing library to Android OS.", | |
| "highlights": [ | |
| "Enabled advanced image manipulation capabilities for mobile developers", | |
| "Gained 200+ GitHub stars", | |
| "Actively used in production applications requiring professional-grade image processing" | |
| ], | |
| "url": "https://github.com/lilac/Android-ImageMagick", | |
| "keywords": [ | |
| "Android", | |
| "ImageMagick", | |
| "Open Source", | |
| "Image Processing" | |
| ] | |
| }, | |
| { | |
| "name": "KubeScript", | |
| "startDate": "2022", | |
| "description": "Founded and currently lead the KubeScript open-source project, a DRY infrastructure-as-code solution that simplifies Kubernetes DevOps workflows.", | |
| "highlights": [ | |
| "Created DRY infrastructure-as-code solution for Kubernetes", | |
| "Reduces configuration complexity for multi-environment management", | |
| "Improves maintainability for teams managing Kubernetes deployments" | |
| ], | |
| "url": "https://github.com/in-fun/KubeScript", | |
| "keywords": [ | |
| "Kubernetes", | |
| "Infrastructure-as-Code", | |
| "DevOps", | |
| "Open Source" | |
| ] | |
| }, | |
| { | |
| "name": "Open Source Contributions", | |
| "description": "Contributed to various open-source projects.", | |
| "highlights": [ | |
| "Rust programming language", | |
| "TensorFlow", | |
| "Helidon web server" | |
| ], | |
| "keywords": [ | |
| "Open Source", | |
| "Rust", | |
| "TensorFlow", | |
| "Helidon" | |
| ] | |
| } | |
| ] | |
| } |
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