# Jinze Huang > Machine Learning Engineer | NYU’ 25 | Ex-Pfizer “Breakthroughs that change patients’ lives” Location: Sunnyvale, California, United States Profile: https://flows.cv/jinze 🚀 Recent NYU CS graduate passionate about building scalable software systems. As a Software Development Engineer, I specialize in designing and implementing robust backend services, distributed systems, and cloud infrastructure. My experience spans from building APIs serving 10K+ requests/day to managing HPC clusters and developing production-ready applications. 💡 Core Expertise: - Software Development: Python, Java, System Design, Design Patterns - Backend Engineering: RESTful APIs, Microservices, Django, FastAPI - Infrastructure: Docker, Kubernetes, Cloud Services (AWS/Azure), CI/CD - Data Systems: PostgreSQL, Redis, Data Pipelines, Distributed Systems - Software Engineering: Code Reviews, Testing, Documentation, Agile 🏆 Impact Highlights: - Developed end-to-end software solutions serving 10K+ users - Built scalable backend systems processing 100GB+ data daily - Reduced system latency by 40% through architectural improvements - Led development of production applications from design to deployment - Published research and hold 2 patents in software applications 📍 Based in Bay Area | Open to SDE, Backend Engineer, and Infrastructure roles ## Work Experience ### Software Engineer @ Smule, Inc. Jan 2025 – Present - Autonomous Agent System (LangGraph): Engineered a multi-agent framework that orchestrates cross-platform data scraping and real-time anomaly investigation within time-series databases. Developed a Reasoning Agent to autonomously pull event data, execute multi-model anomaly detection, and perform multi-dimensional root-cause analysis (RCA). This system evolved from synthesizing product advice to a mission-critical tool adopted by the PM team for automated daily insights and system health monitoring. - Interactive Analytics Platform: Developed a high-performance dashboard to visualize social media trends and automated anomaly diagnostic reports. Integrated unsupervised clustering for feedback themes with advanced time-series analysis to detect emerging market signals and database irregularities. Engineered a self-service alerting pipeline that transforms raw event spikes into actionable visual insights, facilitating rapid cross-team response to market and system shifts. - ML Infrastructure & Optimization: Orchestrated the deployment and fine-tuning of custom-trained models on third-party GPU cloud providers. ### AI Engineer @ SRI Jan 2025 – Jan 2025 | Menlo Park, CA - Multi-Modal Agent Architecture: Orchestrated a suite of perception tools within a LangGraph framework, integrating YOLO for object/person tracking, Whisper for speech transcription and VLM analysis, effectively empowering LLMs to "see" and "hear" raw video data. - Dynamic Query Routing: Designed an intelligent decision-making layer that classifies user intent and dynamically routes queries to specialized sub-agents. This optimized system performance by handling simple tasks locally while reserving complex reasoning for advanced tool chains. - Semantic Video Retrieval: Built a searchable media library enabling users to query video content via natural language. Implemented vector-based indexing to allow precise retrieval of specific video segments and timestamps based on visual and audio keywords. ### AI Engineer @ Canyon Code Jan 2025 – Jan 2025 | Menlo Park, CA - Multi-Modal Agent Architecture: Orchestrated a suite of perception tools within a LangGraph framework, integrating YOLO for object/person tracking, Whisper for speech transcription and VLM analysis, effectively empowering LLMs to "see" and "hear" raw video data. - Dynamic Query Routing: Designed an intelligent decision-making layer that classifies user intent and dynamically routes queries to specialized sub-agents. This optimized system performance by handling simple tasks locally while reserving complex reasoning for advanced tool chains. - Semantic Video Retrieval: Built a searchable media library enabling users to query video content via natural language. Implemented vector-based indexing to allow precise retrieval of specific video segments and timestamps based on visual and audio keywords. ### HPC Systems Engineer @ China Agricultural University Jan 2020 – Jan 2024 | Beijing, China - Managed multi-user HPC platform supporting 20+ concurrent AI/ML workloads - Designed resource monitoring and job scheduling system for optimal cluster utilization - Implemented containerized environments using Docker Swarm for reproducible research - Built backend APIs for HPC management platform improving operational efficiency - Administered Linux servers and storage infrastructure for research teams Tech Stack: Linux, Docker, Python, HPC, Distributed Systems, Infrastructure Management ### Large Language Model Researcher @ China Agricultural University Jan 2023 – Jan 2024 | Beijing, China - Architected scalable data ingestion pipeline processing 100GB+ agricultural data daily with integrated OCR services - Designed and implemented RESTful APIs handling 10K+ requests/day using Django REST Framework - Built microservices architecture for ML model serving, reducing inference latency by 40% - Developed distributed data processing system for knowledge graph with 100M nodes - Managed deployment infrastructure using Docker and Kubernetes Tech Stack: Python, Django, PostgreSQL, Docker, Kubernetes, Microservices, REST APIs ### ML Infrastructure Engineer @ China Agricultural University Jan 2022 – Jan 2023 | Beijing, China - Deployed optimized ML models on edge devices (NVIDIA Jetson) for real-time inference - Built backend services for IoT data collection and processing via 5G/WiFi - Implemented model optimization pipeline using ONNX and OpenVINO - Designed distributed system for agricultural monitoring across multiple sites - Created containerized deployment workflows for edge computing infrastructure Tech Stack: Python, Edge Computing, Docker, Model Optimization, Distributed Systems ### Agricultural CV Researcher @ China Agricultural University Jan 2020 – Jan 2022 | Beijing, China • Spearheaded the development of an apple leaf disease detection system, overseeing the entire lifecycle from data collection to deployment. • Collected and managed a comprehensive dataset of 20,000 high-resolution images, enhancing disease detection accuracy. • Engineered a YOLO-based detection model achieving 0.97 precision and 0.91 mAP50, tailored for agricultural environments. • Implemented advanced model optimization techniques for efficient real-time edge computing deployment. ### Data Infrastructure Engineer Intern @ Pfizer Jan 2022 – Jan 2022 | Chaoyang District, Beijing, China - Built robust data pipeline processing healthcare records for ML applications - Designed backend services for clinical decision support system using Python and SQL - Implemented data validation and ETL processes ensuring data quality and compliance - Collaborated with ML team to deploy models in production environment Tech Stack: Python, SQL, PostgreSQL, Azure, Data Pipelines, ETL, Django ### UNAIDS - Data Engineering Intern @ UNAIDS Jan 2022 – Jan 2022 - Built data collection pipeline processing 1,000+ survey responses for public health research - Designed and implemented ETL workflows for statistical analysis using Python and SQL - Developed automated data validation and cleaning processes ensuring data integrity - Created regression models analyzing health trends, deployed via RESTful APIs - Optimized data processing pipeline reducing analysis time by 60% Tech Stack: Python, SQL, Data Pipelines, ETL, Statistical Modeling, API Development ### ML Infrastructure Engineer Intern @ Chinese Academy of Sciences Jan 2022 – Jan 2022 | Beijing, China - Built ML model deployment pipeline for 3D reconstruction system using PyTorch - Optimized model inference using CUDA/cuDNN, achieving 3x performance improvement - Designed data preprocessing pipeline handling 750+ high-resolution images - Implemented model serving infrastructure for internal research platform - Containerized ML workflows using Docker for reproducible deployments Tech Stack: Python, PyTorch, CUDA, Model Optimization, Docker, ML Infrastructure ## Education ### Master of Computer Science in Computer Science New York University ### Bachelor of Engineering - BE in Computer Science China Agricultural University ## Contact & Social - LinkedIn: https://linkedin.com/in/jinze-huang --- Source: https://flows.cv/jinze JSON Resume: https://flows.cv/jinze/resume.json Last updated: 2026-04-10