Shivam Rawat

AI/ML Engineer with 1.5 years of building AI systems and backend infrastructure. Specialized in developing TTS, ASR, and S2S applications. Proven track record shipping real-time systems, reducing processing latency by 60%, and improving system reliability by 30% through optimized pipelines and scalable backend architecture.

ML/AI Solution Architect at Dave AI (2025-05 – 2026-02)

Architected and built end-to-end conversational AI systems with production reliability patterns and multi-language support.

• Built an end-to-end conversational AI system connecting S2S models with telephony platforms (Twilio and Tata Tele) for real-time voice communication, maintaining 95% uptime
• Created scalable backend with 10+ REST API endpoints for ML model serving, implementing validation, error handling, and structured logging
• Cut TTS and ASR processing time from 3+ seconds to 1-2 seconds by optimizing model pipelines and backend workflows
• Implemented production reliability patterns (connection pooling, circuit breakers, retry logic) ensuring system stability during failures
• Developed Gryd-based caching layer reducing query response times from seconds to milliseconds and backend load by 40%
• Split "Synthesis Main" into GPU and non-GPU microservices, enabling independent scaling and reducing compute costs by 25%
• Set up audit logging and cost tracking to monitor model performance, API errors, and spending in real-time
• Shipped ASR, S2S, Translation, and TTS models supporting 10+ languages including multiple Indian accents
• Gave 3+ technical demos to clients and wrote documentation (API specs, deployment guides) for team onboarding

ML Intern at Dave AI (2024-08 – 2025-05)

Contributed to speech AI systems development with focus on framework migration and language model expansion.

• Led migration from Celery to in-house Gryd framework, enabling consistent task execution across local, UAT, and production environments
• Improved task management and API efficiency, boosting system reliability by 30%
• Added emotion support to TTS models and expanded language support to 10+ Indian languages and accents
• Built Gryd tasks automating natural language to SQL query conversion for Data Insights project
• Created benchmarking framework for comparing and selecting data insight models
• Set up Docker environments and database-driven config management for dynamic model fetching
• Worked with senior engineers on CI/CD pipelines, model optimization, and technical documentation

B.Tech in Computer Science (AIML) – GL Bajaj Institute of Technology & Management (2022 – 2025)