Experienced Machine Learning (ML) Engineer (Data Science, Generative AI and Software/Full-Stack). MEng Computer Science graduate at University College London. Fluent in English, Chinese and Malay. Open to roles in ML/AI Engineering, Data Science and Full Stack. Acquired Microsoft certifications of AI-900, AI-102 and DP-900.
Education
- Minor in Intelligent Systems
- Integrated Masters - Direct continuation from Bachelor's Degree
- Treasurer of UCL Portuguese Speaking Society 22/23
- Computer Graphics: Ray Tracing, Rasterization and Path Tracing with C++.
- Robotics: Forward and Inverse Kinematics, Path Planning and Robot Dynamics with ROS.
Experiences
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LLM Interface: Built the in-browser developer environment — terminal (streaming output, scrollback, tab-completion), code editor with live execution, and a persistent CodeSandbox-backed file system with Google Drive sync.
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AI Assistant Communications: Architected the omni-channel communications infrastructure powering the AI assistant — voice calls, muli-channel messaging, emails, etc. — integrating Twilio, LiveKit and third-party APIs.
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AI Desktop & Browser Control: Built a vision-based (VLM) computer-use agent that automates tasks across remote Ubuntu, Windows and macOS desktops, with CLI-installable clients for connecting a user's own machine.
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Organisation Support: Built multi-tenant organisation features on top of personal workspaces — member management and invites, role-based access control with custom roles, ownership transfer, and project/resource sharing.
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Integrations: Designed a reusable OAuth integration framework and connectors with per-assistant connect/disconnect flows.
- Tech Stack: Python, TypeScript, Node.js, React.js, Next.js, FastAPI, PostgreSQL, Docker, Kubernetes, GCP, Playwright, Git
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End-to-end model development and deployment, such as data analysis, model training, hyperparameters tuning, model selection and cloud deployment on Azure.
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Worked with linear models, trees, random forest, XG boost and light gradient boosting machine (LGBM).
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Pipeline External Corrosion: ML. Built pipeline external corrosion depth & length prediction models of >90% accuracy.
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Pipeline Freespan Formulation: ML. Built subsea pipeline height & length prediction models of >70% accuracy.
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HIP: Computer Vision. Worked on working person detection through object detection with YOLO, pose estimation and vLLM with GPT4o. Involved prompt engineering for better inference performance.
- Tech Stack: Python, MLFlow, Docker, SQL, Azure, SonarCloud, DevOps, Git
Projects
September 2023 - April 2024
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Review Paper. Studied existing tech related to image and music generations, majority being text-conditioned.
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Overview Paper. Developed POCs for Diffusion based Music-conditioned Image Generative AI and Transformer based Image-conditioned Music Generative AI.
- Tech Stack: Python, Pillow, NumPy, SciPy, PyTorch, Transformers, Diffusers, Matplotlib, Git
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Applied PageRank and HITS for analysing key driver in the evolution network.
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Analysed the community structure of the network with modularity.
- Tech Stack: Python, NetworkX, NumPy, Matplotlib, Git
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Explored the effect of different RL algorithms in competitive vs. cooperative MARL settings.
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Algorithms: Advantaged Actor-Critic (A2C), Deep Deterministic Policy Gradient (DDPG), Proximal Policy Optimisation (PPO)
- Tech Stack: Python, OpenAI Gym, Stable Baselines 3, Pandas, Git
Tech Stack
os
framework
cloud/web
others
Languages
Fluent
English, Chinese, Malay
Limited
Korean, Japanese