scott-k.dev
software engineer — AI systems, robotics & infrastructure
Hull, UK
projects
building
System Zero
Self-hosted AI platform. Hybrid semantic search over your own documents, multi-turn reasoning, Text-to-SQL, and a streaming chat interface — all running on local LLMs via llama.cpp.
FastAPI llama.cpp k3s RabbitMQ FAISS React
currently: polish
visit
in progress
Drone RL
Quadcopter hover and target-tracking agent trained with Soft Actor-Critic and Prioritized Experience Replay inside a PyBullet physics simulation. Training metrics streamed live via MLflow.
PyTorch SAC+PER PyBullet MLflow Gymnasium
currently: test
visit
planned
RLxNEAT
Neuroevolution of Augmenting Topologies combined with reinforcement learning reward signals. Evolves both network topology and weights to solve sparse-reward control problems.
NEAT Reinforcement Learning Python Evolution
currently: dev
planned
lab
>
explore
about
Scott K
Building AI systems and infrastructure that actually run — on your hardware, under your control. Interested in reinforcement learning, robotics, distributed systems, and the full stack from silicon to UI.

Everything here is self-hosted.
github.com/Kikumu
cv
experience
AI Agent Engineer Oct 2020 — Present
  • Built production AI agents with reasoning, planning, and autonomous execution using Azure AI and Anthropic Claude — multi-step tool-calling via MCP with FastApiMCP and explicit operation routing.
  • Engineered hybrid RAG pipeline combining FAISS dense vector search with BM25 sparse retrieval, delivering a 40% improvement in retrieval precision through systematic evaluation.
  • Led end-to-end deployment of 3 concurrent production AI applications — GitHub Actions CI/CD, k3s cluster management, KEDA autoscaling, Prometheus + Grafana observability.
  • Self-hosted GGUF inference via llama.cpp on CPU-only VPS; built a real-time SSE streaming gateway and multi-service platform with FastAPI and RabbitMQ.
  • Applied LoRA/PEFT fine-tuning to adapt foundation models (OpenAI, Anthropic, Llama, Qwen) for domain-specific production tasks; managed token budgets and latency constraints.
technical skills
AI Agents Multi-agent architectures, MCP, tool orchestration, planning/reasoning agents, prompt engineering
RAG & Retrieval FAISS, BM25 hybrid search, semantic chunking, re-ranking, retrieval evaluation, SentenceTransformers
Languages Python (expert), TypeScript, C#, SQL, Bash
Backends FastAPI, FastApiMCP, SSE, JWT Auth, RabbitMQ, MySQL, PostgreSQL
Infrastructure Docker, Kubernetes / k3s, GitHub Actions, Azure (AKS, ACR, AzureML, Key Vault)
ML / RL PyTorch, SAC, TD3, PER, DroQ, PyBullet, LoRA / PEFT, llama.cpp GGUF, MLflow
education & certifications
BSc (Hons) Computer Science, 2:1 2020
University, UK — Honours Project: Autonomous Pathfinding Robot (First Class)
Microsoft Certified: Azure AI Engineer Associate (AI-102) Microsoft Certified: Azure AI Fundamentals (AI-900) | Azure Fundamentals (AZ-900) Modern Reinforcement Learning: Actor-Critic Algorithms (Coursera)