AI Systems Engineer
Applied AI work across model training, product engineering, and deployment.
I work across the practical parts of AI: training models, building data and retrieval pipelines, integrating models into products, and keeping the services reliable enough to use.
Training, evaluation, computer vision experiments, and model behavior checks
Document pipelines, embeddings, search quality, and vector databases
APIs and services that connect AI features to real application workflows
Local serving, deployment, monitoring, debugging, and operational cleanup
Local LLM runtime with an OpenAI-style API for offline or private deployments
Model training and computer vision work on subtle facial movement in short video clips
Install and deployment tooling for retrieval systems that use documents and images