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AI Engineer with less than a year in ML systems and LLM applications.
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI / Machine Learning Engineer with experience building end-to-end ML systems including data preprocessing, model training, evaluation, and scalable deployment. Skilled in Python, PyTorch, TensorFlow and LLM-based Application Such as RAG and embedding.
Pimpri Chinchwad University, Pune
Master of Computer Applications
August 1, 2024 – June 1, 2026
Mahatma Gandhi Kashi Vidyapith (MGKVP), Varanasi
Bachelor of Computer Applications
September 1, 2020 – September 1, 2023
LLM-Integrated Learning Assistant
August 1, 2025 – September 1, 2025
Implemented Q&A/explain/quiz flows grounded to curated notes with content-safety checks. Exposed REST endpoints; added rate-limit guards and basic usage analytics. Improved user thumbs-up rate by ~10–12% via prompt and context-window tuning.
Real-Time Object Detection & Alert System
March 1, 2025 – April 1, 2025
Built YOLOv4 + OpenCV microservice behind FastAPI; streamed detections via WebSockets. Optimized preprocessing/IO to cut alert latency from ~1.2s to <400ms on commodity hardware. Reduced false positives by ~15–20% using confidence calibration + rule-based filters.
Hybrid Music Recommendation
February 1, 2025 – March 1, 2025
Engineered lyrics/genre features and metadata embeddings for candidate generation and ranking. Added re-ranker + deduplication to boost top 10 hit-rate by ~10-12%. Published a clean API contract for UI integration.
Housing Price Prediction Pipeline
January 1, 2025 – February 1, 2025
Built reproducible ETL: imputation, outlier handling, scaling, feature selection. Benchmarked Ridge/Lasso/Random Forest; reported MAE/MAPE with K-fold CV. Tracked experiments in MLflow; packaged the model for REST inference.
Machine Learning Specialization
DeepLearning.AI, Coursera
January 1, 2025 – Present
Data Science & ML Bootcamp
Udemy
January 1, 2025 – Present
Azure Machine Learning
Microsoft, Coursera
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and foundational skill set in various AI/ML domains, aligning well with an AI Engineer role. The diversity of projects (LLM, Object Detection, Recommendation, Regression) indicates a broad technical curiosity and adaptability. The certifications further reinforce a proactive learning attitude. However, the lack of professional experience means cultural fit in a corporate setting is yet to be proven.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems and deliver measurable improvements. Participation in co-curricular activities suggests teamwork and coordination skills. However, without specific behavioral assessment data, a comprehensive evaluation of soft skills and operational fit is limited.