Servicenow, Machine Learning, Artificial Intelligence, C++, Google Cloud, Tensorflow, Data Science, Git, Pytorch, Gcp, Python, RAGAS, Architect, Consulting, experimentation

Java, Sql, MLops, Python, LangChain, LLaMA, Data preprocessing, LLMOps, Claude, Pinecone, vLLM, Feature engineering, LMDeploy, LangGraph, FAISS, Milvus, OpenAI, Gemini, Weaviate, Model evaluation

Prometheus, Grafana, Kubernetes, Python, RDMA, GitOps, Go, NVSwitch, Volcano, NVIDIA NVL72 GB300, OpenTelemetry, KAI, NVLink, GPU scheduling, YuniKorn, Kueue, Slurm

Tensorflow, Cloud Services, Pytorch, Python, machine learning frameworks, AI-based video processing, DevOps practices, Azure AI, video analytics

API design, Data Architecture, Microservices, LLM integration patterns, Prompt engineering, Model-agnostic abstraction layers, Containerisation, RAG architectures

Databases, Apis, Distributed Systems, System Design, AI reliability evaluations, production risks, message queues, LLM products, product analytics, Infrastructure, Caching, frontend systems, agentic AI systems, prompting, RAG, guardrails

data engineering , ML Libraries (scikit-learn), Version Control (Git), PyTorch), Containerization (Docker), Deep Learning Frameworks (TensorFlow, Data Processing (pandas, Orchestration (Kubernetes), NumPy), Java, Spring Boot, Python, Machine Learning, Distributed Systems, Artificial Intelligence, Restful Services, Agentic AI, Microservices Architecture, API Design Principles, Event-driven Architectures

Machine Learning, Distributed Systems, Saas, tool integration, retrieval-based architectures, orchestration technologies, modern LLMs, prompt optimisation, Ai, AI agents, architectural standards

Cloud Architecture, Devops, Git, Pandas, MLops, Gcp, Docker, FastAPI, Azure, Python, vector search, reranking models, unstructured data embedding, LLM applications, Langfuse, RAG, document parsing