MLOps and LLM • Reasoning Systems • Inference Optimization • Responsible AI • Scalable AI Engineering
I lead ,design and operationalize large-scale AI and Agentic systems at the boundary between research and production.
- AI Engineering with LLM/VLM
- Ops-MLOps,LLMOps and AgentOps
- Scaling reasoning capability in LLMs
- Engineering efficient training & inference stacks
- Evaluating and monitoring AI systems in production
- Understanding model internals (interpretability & transparency)
- Mechanistic Interpretability
- Building governance-aware AI infrastructure
- Reinforcement Learning
- High-performance LLM inference (vLLM, quantization, memory optimization)
- Distributed training (FSDP, DeepSpeed, Ray)
- Kernel-aware GPU optimization
- Observability & tracing for agentic systems
- LLM evaluation & benchmarking frameworks
- AI governance lifecycle: tracking → evaluation → monitoring → risk controls
If you're working on:
- MultiAgent Evaluation
- Frontier reasoning models
- Agentic AI infrastructure
- Scalable LLM inference stacks
- Mechanistic interpretability
- Governance-aware AI systems
I’m open to serious technical collaboration. Feel free to buzz !