AI Engineer with less than a year in IoT Application Development & Machine Learning
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Final-year B.Tech graduate in Computer Science (AI & ML). Strong foundation in machine learning, generative AI, and data engineering. Proven ability to build end-to-end AI systems - LLM-powered RAG pipelines, agentic AI agents, real-time voice assistants, and computer vision models. Proficient in Python, SQL, LangChain, and AWS. Hands-on exposure to the full data lifecycle: ingestion, transformation, analysis, and visualization.
Deogiri Institute of Engineering and Management Studies
B.Tech · Computer Science (Artificial Intelligence & Machine Learning)
August 1, 2021 – June 30, 2025
Sarosh Jr. College
HSC
June 1, 2019 – May 31, 2021
SDLC Corp
Software Development Intern
February 1, 2025 – July 1, 2025
India
Movie Agent - AI-Powered Screening & Seat Availability System
June 1, 2025 – Present
Built natural-language query system for real-time movie showtimes and seat availability using Llama 3.2 embeddings — processed 100+ test queries with 92% intent accuracy Designed local vector search pipeline, eliminating 3rd-party API dependency and reducing query latency by ~40% via optimised chunking strategy Deployed RESTful Flask backend with responsive frontend UI; system handled 50+ concurrent queries reliably in self-hosted environment
LiveKit AI Voice Assistant
June 1, 2025 – Present
Built real-time AI voice assistant integrating OpenAI LLM, STT, and TTS via LiveKit — achieved end-to-end response latency under 200ms Supported 5+ home automation commands per session including room temperature control, contextual follow-ups, and multi-turn dialogue
View ProjectAutomatic Ambulance Detection System
June 1, 2025 – Present
Trained object detection model on 1,200+ image dataset of emergency vehicles — achieved 89% precision across varied lighting and traffic conditions Integrated model with traffic signal control logic, automating green-light priority for ambulances and cutting simulated emergency response delay by 35%
Cultural Fit Analysis
The candidate's academic projects show a diverse application of AI/ML, from natural language processing to computer vision and real-time voice assistants, indicating a broad interest and adaptability. The internship experience in IoT application development further diversifies their technical exposure. This breadth of experience and willingness to tackle different problem domains suggests a good cultural fit for an innovative and dynamic AI engineering environment.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through project implementations, focusing on performance optimization (latency reduction, accuracy improvement). Collaboration experience in a 4-member team for an internship project indicates good teamwork potential. The academic background in AI & ML aligns well with the target role, suggesting a proactive learning attitude.