Help & Supportcareers@gravityer.com
AI Research Engineer with 1+ years in Machine Learning, Deep Learning & Computer Vision.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Shreyas Murthy is an aspiring AI Research Engineer with 1.7 years of experience in Machine Learning, Deep Learning, NLP, and Computer Vision. Currently pursuing a Bachelor of Technology in Computer Science & Engineering, Shreyas has developed automated computer vision pipelines for colony counting, optimized detection models for Edge AI, and implemented RESTful API endpoints for AI-powered platforms. Their project experience includes bacterial colony enumeration and sentiment analysis, demonstrating strong skills in Python, PyTorch, TensorFlow, and OpenCV.
Dayananda Sagar University
Bachelor of Technology · Computer Science & Engineering
August 1, 2022 – June 30, 2026
AikNov Tek Technologies Pvt. Ltd. (AikyaNova)
Applied AI Systems Intern
November 1, 2025 – Present
Bengaluru, Karnataka, India
Syntech Bio Solutions
ML Research Intern
May 1, 2025 – November 30, 2025
Bengaluru, Karnataka, India
Authify
ML Intern
February 1, 2025 – May 31, 2025
Bengaluru, Karnataka, India
Automated Bacterial Colony Enumeration and Classification
June 15, 2026 – Present
Developed computer vision models for automated bacterial colony counting, transitioning from CNNs to YOLOv8/v9 and achieving real-time detection with 98% precision and 96% recall. Designed and optimized an end-to-end preprocessing and training pipeline using OpenCV, augmentation, and a YOLOv9e two-stage strategy, improving robustness and rare-class detection accuracy.
View ProjectFootball Commentary Sentiment Analysis
June 15, 2026 – Present
Developed an end-to-end NLP pipeline for analyzing football commentary audio using automated speech-to-text transcription with Whisper. Performed player name normalization using regex and applied spaCy-based NLP preprocessing including tokenization, lemmatization, and stopword removal. Mapped player mentions to contextual sentences and performed sentiment scoring using VADER. Used Python, Whisper, yt-dlp, FFmpeg, spaCy, pandas, and VADER for audio processing, NLP preprocessing, and sentiment analysis.
View ProjectCultural Fit Analysis
The candidate's project diversity, including bio-informatics, sports analytics, and educational platforms, indicates adaptability and a broad interest in applying AI across different domains. Their experience in both research and applied AI roles aligns well with the dynamic nature of an AI Research Engineer position. The use of various tools and frameworks suggests a willingness to learn and integrate new technologies.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex project implementations and an ability to work with diverse datasets and technologies. Their internship experiences suggest a proactive and research-oriented approach. The project descriptions indicate good communication of technical details and outcomes.