Contact
+1 (201)-713-1848
jesseqin.office@gmail.com
Manhattan, New York, USA
Key Skills
- AI & Machine Learning Systems
- Scalable TechOps & Infrastructure
- Recommendation Engine Development
- Strategic Project Execution
- Cross-functional Team Leadership
- Cybersecurity & System Reliability
- Data Engineering & Analytics
- Cloud Platforms (AWS, GCP)
Education
Ph.D. in Computer Engineering
Rutgers University, GPA: 3.8, 05/2021
Master of Science in Business Analytics and AI (MSBAi)
NYU Stern School of Business, 05/2025
Master of Science in Computer Engineering
Rutgers University, GPA: 3.8, 05/2016
Certifications
Project Management Professional (PMP)
Issued by Project Management Institute
Date of Issuance: August 2023
Awards & Honors
Rutgers ECE Capstone Top Ten Winner
Rutgers University | May 2014
ISA Process Measurement and Control Scholarship
ISA PMCD | December 2013
Professional Affiliation
Member, Project Management Institute (PMI)
Languages
● English (Professional)
● Chinese (Native)
Professional Summary
Versatile AI technologist and platform strategist with 8+ years of experience building scalable infrastructure, recommendation systems, and GenAI-powered products. Ph.D. in Computer Engineering and MSBA in AI from NYU Stern. Proven success driving 0→1 product launches, leading cross-functional teams, and aligning technical vision with business goals. Fluent across backend, GenAI agent design, distributed systems, and AI-driven business strategy.
Professional Work Experience
Koodall AI Inc.
Vice President of TechOps
Providence | 04/2024 - Present
- Built and launched a stable, scalable backend for FaceAR SDK, GenAI editor, and recommendation engine, supporting real-time AI inference and future scaling.
- Designed cloud architecture (Python, FastAPI, Docker, AWS) that reduced setup time by 40% and ensured production-grade reliability.
- Led cross-functional collaboration (engineering, product, design, sales), speeding product iteration cycles by 30%.
- Established full-stack observability (monitoring, cost dashboard, audit logging), improving operational efficiency by 25%.
- Acted as technical lead and project owner, ensuring smooth planning, delivery, and post-launch optimization.
GETTR USA
Director Of TechOps
Manhattan, NY, USA | 01/2023 - 03/2024
- Redesigned global cloud infrastructure, achieving 99.99% uptime and cutting IT costs by $500K in 3 months.
- Led SRE and DevOps operations, improving incident response speed by 45% through monitoring and replication systems.
- Streamlined backend support for moderation, trust & safety, and mobile release teams, reducing processing time by 35%.
Senior Data Analytics Engineer
Manhattan, NY, USA | 03/2022 - 12/2022
- Designed and deployed a hybrid recommendation engine (user behavior, content similarity, social graph), boosting engagement by 43% and doubling video watch time.
- Built BI dashboards for MAU, DAU, retention, enabling data-driven leadership decisions.
Backend Engineer
Manhattan, NY, USA | 05/2021 - 02/2022
- Built Elasticsearch-based search and data pipelines from scratch, scaling GETTR to over 1M users within 3 days of launch.
Rutgers Informatics Discovery Institute
Graduate Assistant
New Brunswick, NJ, USA | 09/2015 - 05/2021
- Developed distributed workflows for real-time analytics, supporting national science observatories (OOI, GAGE).
- Contributed to Rutgers HPC cluster (#167 in Top500) deployment and optimization, enhancing multi-disciplinary compute capacity.
- Published 7+ peer-reviewed papers on distributed caching, workflow scheduling, and infrastructure innovation.
Publications
- Toward Democratizing Access to Facilities Data: A Framework for Intelligent Data Discovery and Delivery, IEEE CiSE
- Leveraging User Access Patterns and Advanced Cyberinfrastructure to Accelerate Data Delivery, FGCS
- Facilitating Data Discovery for Large-scale Science Facilities using Knowledge Networks, IPDPS
- Enabling Data Streaming-based Science Gateways through Federated Cyberinfrastructure, Gateways
- Towards a Smart, Internet-scale Cache Service for Data Intensive Scientific Applications, ACM SCC
- Exploring Power Budget Scheduling Opportunities and Tradeoffs for AMR-Based Applications, SBAC-PAD
- Cloud-based Data Analytics Framework for Autonomic Smart Grid Management, IEEE CAC