AI Engineer with 3+ years in Generative AI & Machine Learning
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Assessing your cultural and operational fit
Experienced AI Engineer with 3.4 years of expertise in architecting real-time AI platforms and developing low-latency inference pipelines. Proficient in Generative AI, Machine Learning, and DevOps technologies, specializing in multimodal AI systems, NLP pipelines, and data-driven solutions. Proven ability to optimize model performance, reduce latency, and ensure high availability in production environments.
Michigan Technological University
Masters of Science · Data Science
August 1, 2023 – April 1, 2025
Savitribai Phule Pune University
Bachelor of Engineering
January 1, 2017 – January 1, 2021
Realfy Inc
AI Engineer
October 1, 2025 – May 1, 2026
India
Michigan Technological University
Graduate Research Assistant
December 1, 2023 – October 1, 2025
India
Fyle Technologies
Software Engineering Intern
October 1, 2021 – April 1, 2022
India
Real-Time Voice AI Agent Platform
June 1, 2026 – Present
Architected a real-time, full-duplex speech-to-speech conversational AI system, enabling low-latency voice interactions across dynamic user workflows. Designed streaming pipeline: ASR → LLM reasoning → TTS, supporting interruptible conversations and context-aware responses. Implemented LLM-powered agent orchestration using LangChain/LangGraph, enabling tool-calling, memory retention, and multi-step reasoning. Optimized inference latency using PyTorch + ONNX + FP16 batching, reducing response time to <600ms for end-to-end voice responses.
View ProjectLow-Latency AI Inference & Backend System
June 1, 2026 – Present
Implemented GPU-optimized inference pipelines using PyTorch and TensorRT, reducing latency by 35%. Developed async REST APIs using FastAPI and asyncio, increasing request handling capacity by 70%. Integrated PostgreSQL and Redis caching layers, decreasing response time by 40%. Automated CI/CD pipelines with Docker and Kubernetes, improving deployment frequency by 3x.
DyGAF Model: A Novel Dynamic Gene Attention Focus Approach for COVID-19 Biomarker Ranking.
Bioinformatics and Biology Insights
June 1, 2025 – Present
Cultural Fit Analysis
The candidate demonstrates a strong cultural fit for an AI Engineer role, particularly in a fast-paced, innovation-driven environment. Their projects showcase a proactive approach to tackling complex, real-world problems (e.g., real-time voice AI, low-latency inference). The breadth of technologies used (PyTorch, FastAPI, Kubernetes, LangChain, ONNX, TensorRT, PostgreSQL, Redis, AWS, GCP) indicates adaptability and a continuous learning mindset. The publication also highlights a research-oriented and problem-solving attitude. The focus on performance and scalability aligns well with typical startup or high-growth tech company cultures.
Soft Skills & Operational Fit
The candidate's project and experience descriptions indicate a strong focus on performance optimization, system architecture, and end-to-end solution delivery, which are critical for operational fit in an AI Engineer role. The detailed metrics provided suggest a results-oriented approach. While direct soft skill assessment is not possible from the provided data, the structured project descriptions imply good communication of technical achievements.