Help & Supportcareers@gravityer.com
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer with less than a year in Generative AI, Machine Learning & Deep Learning
Motivated and enthusiastic student with a strong interest in Generative AI, Machine Learning, and intelligent automation. Passionate about exploring how modern AI technologies can be designed to solve complex, real-world problems through data-driven insights and innovative solutions. I enjoy working on hands-on projects in programming, artificial intelligence, and machine learning to strengthen practical skills and translate theoretical concepts into meaningful applications. I'm particularly interested in developing AI-powered solutions that improve efficiency, enhance user experiences, and support smarter decision-making processes. I thrive in collaborative environments, value continuous learning, and actively seek opportunities to deepen my understanding through experimentation, research, and applied exploration. Committed to growing both technically and professionally while contributing meaningfully to innovative and impact-driven teams.
RV University
Bachelor of Technology (Hons.) · Computer Science and Engineering
August 1, 2024 – June 30, 2027
Cluny Convent High School
10th
N/A – Present
Cluny Convent High School
12th · PCMB
N/A – Present
HPCC Systems (LexisNexis Risk Solutions)
Student Internship
June 1, 2024 – August 31, 2024
India
Braille Tutor
June 1, 2026 – Present
Worked collaboratively on an affordable Braille Tutor inspired by Duolingo, aimed at improving literacy for visually impaired students in remote areas. Contributed to research, design, and development using Arduino UNO, ESP32, and the Wokwi Simulator to provide tactile and audio feedback. Addressed hardware compatibility issues and optimized Braille cell coding to enhance learning outcomes, ensuring a smooth and effective learning experience.
Explainable GAN-Based Defect Simulation and Detection
June 1, 2026 – Present
Developed an explainable industrial defect detection framework using a patch-based DCGAN to generate realistic synthetic defects and a custom CNN for accurate classification on the MVTec AD dataset. Applied texture-aware blending techniques to augment limited defect samples and address class imbalance, leading to improved detection performance with accuracy reaching up to 99.13% on object-based categories. Enhanced model transparency by integrating Grad-CAM heatmaps to localize defect regions and SHAP analysis to interpret feature contributions, creating a reliable, interpretable, and industry-oriented defect inspection pipeline.
Sign Language Translation and Gesture Recognition
June 1, 2026 – Present
Developed a lightweight SVM-based model for real-time Indian Sign Language (ISL) gesture recognition, translating hand gestures into text using 3D landmark data. Created a custom dataset containing 6,000 samples of digits and letters and 4,000 samples of 14 common ISL phrases, utilizing OpenCV and MediaPipe for efficient feature extraction. The model achieved 87.94% accuracy for letters and numbers and 89.12% for phrases, providing effective communication support for hearing-impaired users on low-resource devices.
Affective Computing
NPTEL
June 1, 2026 – Present
Software Testing
NPTEL
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse academic projects, including assistive technology and industrial defect detection, show a broad interest in applying AI to various real-world problems. Their involvement in an internship and academic publications indicates a drive for practical application and knowledge sharing. The focus on explainable AI and user-centric solutions suggests an alignment with ethical and responsible AI development, which is a positive cultural fit for many organizations.
Soft Skills & Operational Fit
The candidate demonstrates a proactive and collaborative attitude, as evidenced by their involvement in team projects and internships. Their interest in continuous learning and problem-solving aligns well with dynamic technical environments. The detailed project descriptions indicate good communication skills in conveying technical approaches and results.