Anish Vijayvergiya

WORK HISTORY

EDUCATION

ABOUT ANISH VIJAYVERGIYA

Senior software engineer with 5 years building end-to-end AI solutions—from system design and model training to deployment and scaling—across GenAI, NLP, and predictive analytics. I specialize in production-grade RAG systems, LLM fine-tuning, and cost-efficient MLOps on AWS/GCP.Current Role — Apple (Nov 2025–Present)Working on Apple’s Location Intelligence and Search AI initiatives, designing and optimizing end-to-end GenAI, agentic AI, and ML pipelines that support large-scale geospatial + contextual processing, intelligent search, and model deployment.Previous Role — Globiva (Jan 2025–Oct 2025) • Designed & deployed an enterprise RAG framework (ingestion → chunking → embeddings → hybrid search → reranking → LLM) using ChromaDB, Milvus, Mistral 7B, and LLaMA 13B, improving answer accuracy by 28% and reducing hallucinations. • Deployed GPU-enabled FastAPI microservices on AWS EC2 + Docker, cutting infra spend by 30% and reducing CI/CD cycle time by 40%. • Fine-tuned Whisper ASR for call-center speech, lowering WER by 12%; expanded multilingual PDF QA using EasyOCR + PaddleOCR. • Built an XGBoost attrition-risk API with 90+ HR features, enabling real-time workforce analytics.Core StackPython | PyTorch | TensorFlow | Transformers | FastAPI | Docker | AWS | GCP | ChromaDB | Milvus | Mistral | LLaMA | Whisper | XGBoost | CI/CD | GitPast Highlights • Tata Consultancy Services (2021–2024): Increased chatbot precision by 30% with BERT & GPT-3; automated NLP preprocessing workflows, reducing cycle time by 25%.