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AI Engineer with less than a year in Computer Vision & Generative AI
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Assessing your cultural and operational fit
AI/ML Engineering Student with a focus on building reliable, end-to-end intelligent systems. Proven ability to develop practical solutions in Computer Vision and Generative AI, including optimizing ML pipelines and resolving critical technical bottlenecks in assistive technologies. Proficient in Python and modern frameworks, with a strong emphasis on writing clean, deployable code and improving model performance. Seeking an ML Engineer or AI Associate role to contribute to scalable, high-impact projects.
Acharya Nagarjuna University
B.Tech · Artificial Intelligence & Machine Learning
August 1, 2022 – June 30, 2026
BrainOVision Solutions
Data science Intern
May 1, 2024 – July 1, 2024
India
Multimodal Assistive Communication System
January 1, 2026 – Present
Resolved a critical character-streaming defect by engineering a frame-boundary segmentation algorithm using MediaPipe landmark sequences, achieving a 91.5% Word Error Rate (WER) improvement in real-time lip-reading tasks. Architected a multi-stream system that optimized inference latency by 15% through model quantization and refined the gesture-recognition module to reach a 96% classification accuracy across diverse lighting conditions and user profiles.
View ProjectSelf-Correcting Agentic RAG System
January 1, 2025 – Present
Engineered a self-healing RAG pipeline using reflection loops and Tavily web-verification to cross-reference LLM outputs, achieving a 94% factual accuracy rate on complex domain queries. Developed a hybrid retrieval architecture that combines ChromaDB vector search with real-time web agents, reducing hallucinations by 22% compared to baseline RAG models as measured by an automated LLM-as-a-judge evaluation framework.
View ProjectData Science Virtual Experience Program
British Airways (via Forage)
June 1, 2026 – Present
Software Engineering virtual internship
JP Morgan Chase & co. (via forage)
June 1, 2026 – Present
Multi-Modal Assistive Communication System: Real-Time American Sign Language Recognition, Lip Reading, and Morse Code Translation Using Browser-Based AI.
International Journal for Research in Applied Science and Engineering Technology (IJRASET)
January 1, 2026 – Present
NPTEL Certified: Software Engineering
IIT Kharagpur
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in impactful AI applications (assistive communication, reducing hallucinations). The blend of academic rigor (publications) and practical application (internships, project results) suggests a proactive and learning-oriented individual. The target role of 'AI Engineer' aligns well with their stated skills and project experience. The diversity of projects (CV, NLP, RAG) indicates a broad interest within AI/ML, which is positive for cultural fit in an innovative environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to identify and resolve critical technical defects, optimize systems for performance, and collaborate (as seen in the internship). The focus on 'clean, deployable code' and 'improving model performance' suggests an operational mindset. However, direct evidence of stress handling, team collaboration beyond basic internship interaction, or specific communication styles is limited.