K. Harsha Vardhan Reddy
ML EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
ML Engineer with less than a year in AI/ML Pipelines & NLP
Final-year B.Tech (AI & ML) student with hands-on internship experience at Cognifyz Technologies and strong fundamentals in machine learning, deep learning, NLP, and computer vision. Experienced in building end-to-end AI/ML pipelines spanning CNN-based vision systems, transformer-based NLP, healthcare AI, and data-driven recommendation systems. Seeking roles in ML Engineering or NLP Engineering to contribute to scalable, production-grade AI systems.
Malla Reddy University
B.Tech · Computer Science Engineering (AI & ML)
August 1, 2022 – June 30, 2026
Narayana Junior College
Intermediate (MPC)
June 1, 2020 – May 31, 2022
Unique High School
SSC
June 1, 2019 – May 31, 2020
Cognifyz Technologies
Machine Learning Intern
May 25, 2026 – June 25, 2026
India
Child Adoption Management System
June 1, 2026 – Present
Developed a responsive full-stack web application managing 500+ user records and adoption case workflows with role-based access control. Designed a normalized relational database schema (3NF) and optimized SQL queries (reducing average query time by ~30% via indexing). Demonstrated secure form handling and backend system design.
Text Summarization Model
June 1, 2026 – Present
Developed both extractive (TF-IDF ranking) and abstractive (sequence-to-sequence with attention) summarization models on news article datasets. Fine-tuned a pre-trained BERT-based encoder for abstractive generation, achieving ROUGE-1: 0.41, ROUGE-L: 0.38. Benchmarked multiple approaches and documented trade-offs.
Fire Detection System using Deep Learning
June 1, 2026 – Present
Designed and trained a CNN model to detect fire in real-time video streams, achieving 92%+ accuracy. Built an end-to-end pipeline covering dataset curation, image annotation, augmentation, model training, and inference optimization (reducing false-positive rate by ~18%). Deployed inference on a CPU-only machine at ~15 FPS using OpenCV.
Voice-Activated Calculator
June 1, 2026 – Present
Built a voice-controlled arithmetic application using the SpeechRecognition library and NLTK for intent classification and entity extraction. Improved recognition accuracy from ~74% to 91% by adding audio pre-processing (noise reduction, normalization) and post-processing (spell-correction, regex normalization) stages. Designed a modular NLP pipeline.
Multiple Disease Prediction System with AI Health Assistant
June 1, 2026 – Present
Engineered a unified prediction system covering 3 diseases (Diabetes, Heart Disease, Parkinson’s Disease) using dedicated Scikit-learn classifiers (SVM, Logistic Regression, Random Forest). Achieved Diabetes: 87% accuracy, Heart Disease: 89% accuracy, and Parkinson’s: 91% accuracy. Integrated a rule-based AI chatbot for symptom input and query routing. Built an end-to-end pipeline including data preprocessing, SMOTE, feature importance, model serialization, and a Streamlit web UI. Evaluated models using confusion matrix, precision, recall, F1-score, and ROC-AUC.
Trailhead
Salesforce
June 1, 2026 – Present
AWS Cloud Foundations
AWS Academy
June 1, 2026 – Present
Database
Oracle
June 1, 2026 – Present
Machine Learning Specialization
Coursera / DeepLearning.AI
June 1, 2026 – Present
Natural Language Processing with Classification and Vector Spaces
Coursera
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, covering web development, NLP, computer vision, and healthcare AI, indicates a broad interest and adaptability, which can be a positive for cultural fit in dynamic environments. The target role of ML Engineer aligns well with the candidate's academic background and project focus. The breadth of skills, including both ML/DL and some full-stack development (PHP, SQL), suggests a versatile individual. However, the experience is primarily academic, and the internship is very short, so exposure to corporate culture, long-term project cycles, and cross-functional team dynamics is limited. The certifications in AWS and Salesforce indicate a proactive approach to learning industry-relevant tools.
Soft Skills & Operational Fit
The candidate demonstrates problem-solving skills through iterative optimization in projects (e.g., reducing false positives, improving recognition accuracy). Team collaboration is mentioned as a soft skill, but specific examples of collaboration in projects are limited. Detail-oriented thinking is evident in thorough model evaluation and documentation of trade-offs. The academic nature of most projects suggests a strong learning aptitude and ability to work independently on defined tasks. The short internship provides some exposure to a more structured operational environment.