Resume

Professional Experience

AI Developer & Fund Manager &

June 2024 - Present
Zenith Capital • $10M AUM
San Francisco, CA
  • Manage $10M AI-native quantitative investment fund with full investment authority, responsible for P&L, risk management, and portfolio construction across equities, options, and digital assets
  • Achieve consistent risk-adjusted returns through systematic strategies, maintaining Sharpe ratio >1.5 and max drawdown <15% while managing multi-asset portfolio allocation
  • Own end-to-end product strategy for proprietary AI-powered trading platform serving both internal fund operations and external clients
  • Built production-grade AI agent systems integrating LLMs (OpenAI, Anthropic) with quantitative models for strategy generation, risk monitoring, and portfolio rebalancing
  • Implement comprehensive risk management framework including VaR analysis, factor exposure monitoring, stress testing, and real-time position limits across $10M portfolio
  • Designed and deployed data pipelines processing 10M+ data points daily using Python (pandas, numpy, scikit-learn) and SQL for market data, sentiment analysis, and performance attribution
  • Developed multi-platform trading infrastructure with API integration (Interactive Brokers, Alpaca, Polymarket) supporting automated execution and order management
  • Established KPIs and evaluation frameworks tracking investment performance, model accuracy, execution quality, and risk metrics with daily monitoring dashboards
  • Conducted ongoing market research and strategy validation through 100+ published analyses, incorporating institutional and retail feedback into product roadmap

Founding Product Manager

Mar 2022 to April 2024
TensorOpera AI (previously named FedML)
Palo Alto, CA
  • Owned product strategy, roadmap, and execution for AI/ML products from 0-1 through scale
  • Led cross-functional teams (engineering, research, design, GTM) to deliver AI-powered applications on time
  • Defined success metrics and KPIs, established data-driven decision making processes using analytics and A/B testing
  • Conducted user research, stakeholder interviews, and competitive analysis to inform product vision and prioritization
  • Partnered with engineering teams on technical architecture, API design, and ML model integration decisions
  • Managed stakeholder alignment across leadership, investors, and customers through clear communication of product strategy
  • Drove go-to-market planning including pricing strategy, positioning, and launch coordination

AI Product Manager

2021 - 2022
Alibaba Cloud
Beijing, China
  • Led product management for AI/ML cloud services serving enterprise customers
  • Defined product roadmap and strategy for cloud-based AI platforms and tools
  • Collaborated with engineering teams to deliver scalable AI solutions on cloud infrastructure
  • Conducted market research and customer interviews to identify product opportunities
  • Managed product launches and go-to-market strategies for AI cloud products
  • Worked with cross-functional teams across product, engineering, and business development

Software Engineer

2019 - 2021
CV Engineering
Beijing, China
  • Developed computer vision and deep learning systems for production applications
  • Implemented ML models using PyTorch and TensorFlow for image recognition and analysis
  • Built scalable data pipelines for training and deploying CV models at scale
  • Optimized model performance and inference speed for real-time computer vision applications
  • Collaborated with product and engineering teams to integrate CV solutions into products
  • Contributed to core vision systems serving enterprise customers

Software Engineer Intern

2021
Tencent CV Lab
Shenzhen, China
  • Developed computer vision and machine learning models for production applications
  • Implemented deep learning algorithms using PyTorch and TensorFlow frameworks
  • Built scalable ML pipelines for training and deploying CV models at scale
  • Collaborated with research teams to translate research prototypes into production systems
  • Optimized model performance and inference speed for real-time applications
  • Contributed to core computer vision products serving millions of users

Education

Master of Science in Information Technology

2019-2021
Carnegie Mellon University
Pittsburgh, PA
  • Focus on Software Engineering, Data Analytics, and Machine Learning
  • Specialized in AI/ML systems and quantitative methods

Bachelor of Engineering

2015-2019
Queen Mary University of London
London, UK
  • Strong foundation in computer science and engineering principles
  • Focus on quantitative methods and analytical thinking

Technical Skills

Programming & Data

  • Python: pandas, numpy, scikit-learn, PyTorch
  • SQL: data analysis, query optimization
  • API Development & Integration (RESTful, gRPC)
  • Git, Docker, CI/CD pipelines
  • Data visualization, Jupyter notebooks

AI/ML & Agent Systems

  • LLM Integration (OpenAI, Anthropic APIs)
  • AI Agent Architectures & Multi-agent Systems
  • Prompt Engineering & RAG Systems
  • Model Evaluation & Testing Frameworks
  • ML Pipeline Development & Deployment

Quantitative Finance

  • Portfolio Optimization & Risk Management
  • Options Pricing (Black-Scholes, Greeks)
  • Factor Models & VaR Analysis
  • Market Microstructure & Execution
  • Statistical Modeling & Backtesting

Product Management

  • Product Strategy & Roadmap Development
  • Stakeholder Management & Communication
  • Metrics Definition & Analytics (KPIs, A/B Testing)
  • Cross-functional Team Leadership
  • Technical Requirements & Documentation
  • Agile/Scrum Methodologies

Platforms & Tools

Key Achievements

Languages