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.
| 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, Golang, SQL, Rust, LaTeX |
| 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