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Vladislav Li

Email: couper64@gmail.com | Location: London, UK

Profile

Software Engineer with a PhD in Artificial Intelligence and and extensive hands-on experience designing, deploying, and maintaining ML systems in production. Specialises in containerised infrastructure, distributed backend services, and GPU-based inference pipelines. Comfortable working across the full stack such as from bare-metal server setup and Linux administration through to cloud deployment and ML model integration. Brings both research depth and engineering rigour to building reliable, scalable AI systems.

Skills

MLOps & Infrastructure

  • Docker and Docker Compose — containerised ML service design, multi-service orchestration
  • CI/CD — GitHub Actions, automated build, test, and deployment pipelines
  • Kubernetes — workload deployment and basic cluster orchestration
  • ML model serving — inference pipeline design, GPU workload management, throughput optimisation

Backend Engineering

  • FastAPI, Celery, Redis — distributed APIs, async task queues, message brokering
  • REST API design and microservices architecture
  • Linux systems administration — Ubuntu, Arch, Fedora, Void (scripting, service management, performance tuning)
  • Networking — switches, structured cabling, IP configuration, system integration

Cloud & Infrastructure

  • AWS EC2 — instance provisioning, service deployment, remote access configuration
  • Azure AI Services — integration into backend processing and production ML workflows
  • On-premise GPU server setup and maintenance

Programming

  • Python — primary language for backend systems, ML tooling, and automation
  • C / C++ — performance-critical and systems-level programming
  • C# — application development (Unity, XR platforms)
  • SQL — schema design, normalisation, query optimisation
  • Lua — scripting and rapid prototyping

Experience

Research Engineer — AI Systems & MLOps

Kingston University, London | 2021 – Present

  • Designed and deployed containerised ML inference systems using Docker on Linux servers, enabling reproducible, portable model serving across development and production environments
  • Built distributed processing pipelines using FastAPI, Celery, and Redis to handle concurrent ML inference requests with reliable async task queuing
  • Optimised GPU-based inference to meet real-time performance requirements in industrial simulation contexts
  • Integrated ML model backends with VR/XR platforms (Unity, HoloLens) for EU-funded Industry 4.0 research projects
  • Delivered production-grade backend services for AI workloads with focus on reliability, maintainability, and observability
  • Configured and maintained on-premise Linux servers and GPU workstations supporting research infrastructure

Projects

Distributed ML Inference Platform

  • Designed a horizontally scalable inference API using FastAPI with Celery worker pools and Redis as the message broker
  • Containerised all services using Docker for consistent, reproducible deployment across environments
  • Architected for concurrent workload distribution, separating compute-heavy GPU tasks from lightweight API routing

Cloud AI Deployment (AWS / Azure)

  • Deployed ML inference endpoints on AWS EC2 with automated startup scripts and access control configuration
  • Integrated Azure AI Services into production backend workflows for real-time AI-assisted processing

Industrial XR + AI Integration (EU-funded)

  • Developed Unity-based XR applications that consume ML model outputs for industrial operator training simulations
  • Coordinated ML backend services and XR frontend integration across a distributed research team

Education

PhD in Artificial Intelligence — Kingston University | 2021 – 2024

MSc Games Development (Programming) — Kingston University | 2019 – 2020

BSc (Hons) Computer Science (Games Programming) — Kingston University | 2015 – 2019

Publications

Research in computer vision and efficient AI systems. Full list available on request.

Additional

  • VR/AR development: Unity, Unreal Engine, Microsoft HoloLens
  • Robotics: Unitree platform, Python-based motion control and scripting
  • Hardware: server and workstation build and configuration, GPU setup, structured cabling and network switches