AI/ML Engineer | FinTech | Distributed Systems | Low-Latency Systems
AI/ML Engineer at EEPL, working on production-grade AI and financial systems.
Currently pursuing M.Tech. in IoT & Autonomous Systems at IIIT Sri City.
Chancellor Gold Medalist — Faculty of Engineering & Technology, MGM University.
- AI/ML: LLMs, RAG, NLP, VLMs, Embeddings, AI Agents, PyTorch
- Backend: Python, Go, Rust, C++, TypeScript, FastAPI, Django, NestJS
- Distributed Systems: Microservices, Event-Driven Systems, Distributed Databases
- FinTech: Trading Systems, Financial Workflows, Quantitative Analytics
- Databases: PostgreSQL, ScyllaDB, Cassandra, ClickHouse, Redis, MongoDB, QuestDB
- Infrastructure: AWS, GCP, Oracle Cloud, Docker, Kubernetes, NGINX, CI/CD
- Low-Latency: Aeron, High-Throughput Messaging, Performance Optimization, Red Panda
QuantStream — Distributed Trading & Analytics Platform A microservices-based trading and analytics platform using Aeron, ScyllaDB and ClickHouse for low-latency messaging and high-throughput data processing.
Omni-Channel Voice Agent (Community Edition)
An ultra-low latency, real-time omni-channel voice platform featuring dual AI orchestration engines:
- Local CUDA Stack: Whisper.cpp (CUDA STT) -> Clef-Flash (System One Decision Engine) -> Qwen3-4B -> Kokoro TTS
(100% Free & Local).
- Cloud Indic & HD Stack: Sarvam Saaras v3 -> TypeSafe Jev API -> Sarvam-105B -> Bulbul v3 / ElevenLabs Turbo
v2.5 (BYOK).
- Built with Rust (Axum + AVX2/AVX-512 SIMD DSP), in-browser Silero Neural VAD v5 (WebAssembly), sub-
microsecond in-memory clinical tool dispatch (<1µs), and node-based visual workflow studio designer (TTFS <250ms).
Vector Search Platform A scalable semantic search system using Go, PostgreSQL/PGVector and vector embeddings for large-scale product retrieval.
AI Systems · CUDA · Distributed Systems · FinTech Infrastructure · Low-Latency Computing · Quantitative Finance · Kubernetes · Rust · C++ · IoT & Autonomous Systems · SIMD