Turning models into production systems.
I build, optimize, and deploy machine learning systems at scale.
My focus areas:
- Production ML pipelines
- Multimodal AI systems
- Distributed training & performance optimization
- Inference infrastructure
- Cloud-native ML deployment
- Backend architectures for AI services
I care about:
Performance • Reliability • Scalability • Clean system design
- Real-time inference systems
- Robust multimodal ML services
- Model observability tooling
- Performance-optimized training loops
- AI-backed APIs
- Clean, modular backend systems
- End-to-end ML product ownership
- Designing scalable backend systems for AI products
- Low-latency inference services
- Cloud-native AI architectures
- Production monitoring & model lifecycle management
- Translating research models into deployable systems
