Pytorch, Python, hardware-aware ML optimization, hardware co-design, flow matching, KV cache optimization, sparsity, speculative decoding, custom instrumentation, caching strategies, Nsight, efficient inference techniques, Distillation, state space models, PyTorch Profiler, LoRA adapters, quantization, benchmarking frameworks, applied research, Transformers, attention mechanisms, fine-tuning large models, training evaluation pipelines, Profiling Tools, attention variants, MoE routing, algorithmic acceleration, diffusion models

Devops, Jenkins, Git, Docker, Kubernetes, Python, AgenticAI frameworks, R, AI ML engineering, CI CD tools

product management, data-driven insights, go-to-market strategy, AI technologies

Retrieval-Augmented Generation (RAG), Apis, Backend Development, Distributed Systems, Prompt engineering, Vector DBs, LLM observability tracing tools, Llm, LangGraph, Production-grade software engineering, Hybrid search, AI-native systems, Agentic workflows

data engineering , state management , Orchestration, Java, Amazon Web Services, Machine Learning, Python, Indexing, re-ranking, embedding-based search, grounding methods, data quality controls, idempotent pipelines, retrieval, metadata lineage, applied artificial intelligence, cloud-native services

Visual Studio Code, User Research, Cursor, Prototyping, Ai, Open AI Codex, Claude, Agentic AI tools, Code Claude, Co-work, Lean product management, Competitive Analysis, product vision, GenAI tools