Software Engineer
I build software for machine learning systems, mostly around data, training, inference, and the infrastructure that keeps them running.
Most of my work sits between machine learning and backend systems: tracing, orchestration, reliability, and performance.
Software Engineer, AI Trace Generation
I work on tracing for distributed training and inference across GPUs and clusters. The traces are used in simulations to find bottlenecks and understand where time and compute are being lost.
Multimodal
I worked on a production platform for document workflows, enterprise search, conversational AI, and reporting.
Multimodal
I built core parts of a tool that turns natural-language requirements into AI workflows, including ingestion monitoring, confidence scores, and audit trails.
Go / gRPC
A Go server that adds gRPC streaming and custom backend features around the OpenAI API.
Python / ML
A desktop interface for training pretrained models and following progress in TensorBoard.
I’m interested in ML infrastructure, computer vision, and bio-inspired AI—especially work that has to function outside a research environment.
8th International Conference on Computer Science and Engineering
7th International Conference on Computer Science and Engineering
A little context beyond the work.
Outside of building AI systems, you will find me on the Nürburgring Nordschleife or in a sim, trying to improve every apex and braking point.
I read science fiction and neuroscience papers when I can. The intersection of biological and artificial intelligence continues to shape how I think about better models.
Education
BSc in Computer Engineering
