Help & Supportcareers@gravityer.com
AI Engineer with 3+ years in Generative AI & Machine Learning
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
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.