Machine Learning Architect & Systems Engineer building scalable AI infrastructure, distributed systems, and cloud-native platforms.
I transform research concepts into production systems — prioritizing scalability, reproducibility, and operational excellence.
Every public repo, scored across eight axes (AI/ML, Cryptography, Distributed Systems, Optimization, Algorithms, Production Backend, Frontend, Performance) and rendered as an animated radar. The SVG above draws itself in and sweeps continuously — pure SVG, like Platane/snk.
iframe embed (full Chart.js interactivity on github.com web)
<iframe src="https://sachncs.github.io/sachncs/" width="100%" height="640" frameborder="0" loading="lazy"></iframe>| Area | Focus |
|---|---|
| Promptsheon | Open-source, Git-native infrastructure for versioned and auditable autonomous AI agent configurations |
| AI Infrastructure | Content-addressable storage, LLM lifecycle management, and reproducible agent execution |
| Inference Systems | Performance optimization for vLLM, TensorRT-LLM, and large-scale serving pipelines |
| Optimization Engines | Parallel metaheuristics and distributed computation for complex planning and logistics |
| Distributed Architecture | Event-driven microservices and resilient cloud platforms for regulated domains |
| Category | Skills |
|---|---|
| Programming Languages | Python, TypeScript, Rust, Golang, SQL |
| AI / LLM | PyTorch, TensorFlow, vLLM, Hugging Face, LangChain |
| Cloud & MLOps | AWS, GCP, Kubernetes, Docker, Modal, FastAPI |
| Databases & Observability | Postgres, Mongo, Redis, Weaviate, Elasticsearch, OpenTelemetry |
Machine Learning Systems • Distributed Computing • Generative AI Infrastructure • High-Performance Computing • Cloud Architecture • Open Source
- Reach me at sachncs@gmail.com
- Always happy to collaborate on anything ambitious, weird, or world-changing