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AI Engineer with less than a year in AI/ML and Python ecosystem with deep learning and predictive an
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Computer Science undergraduate specializing in the Python ecosystem with deep competence in building and deploying machine learning logic. Architected custom deep learning pipelines (PyTorch) and high-precision predictive engines (XGBoost), cleanly wrapping complex inference models into highly scalable, asynchronous REST APIs (FastAPI). Backed by rigorous algorithmic consistency (500+ DSA problems solved).
Chandigarh Group of Colleges
Bachelor of Technology · Computer Science and Engineering
August 1, 2023 – June 30, 2027
Neural Audio Fingerprinting (Find Song by Singing)
June 3, 2026 – Present
Architected an end-to-end Deep Learning system capable of identifying specific tracks from raw, unstructured human singing or humming audio. Engineered an automated preprocessing pipeline to transform 1D audio waveforms into 2D Mel-Spectrograms, optimizing data for mathematical representation. Designed and trained a custom Siamese Network in PyTorch, integrating a CNN branch for spatial feature extraction and an LSTM branch for temporal sequence modeling. Wrapped heavy model inference logic into a clean, asynchronous REST API using FastAPI, reducing downstream request bottlenecks for seamless frontend integration.
View ProjectCab Demand Forecasting
June 3, 2026 – Present
Deployed a dynamic pricing model using XGBoost to predict fare surges, achieving high precision by engineering features from temporal and geospatial patterns. Analyzed demand trends across different time zones to identify high-value pickup windows, providing actionable insights for optimal route orchestration. Improved prediction accuracy by engineering cyclical time features and isolating outliers, resulting in a robust R-squared score of 0.89 on unseen test data.
View ProjectAdvanced Training: Comprehensive Data Science, ML, DL & NLP intensive
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and initiative in advanced AI/ML topics, aligning well with an AI Engineer role. The diversity in project types (forecasting, audio processing) shows a breadth of application interest. The self-driven achievement in solving 500+ DSA problems indicates a strong work ethic and commitment to continuous learning, which are positive indicators for cultural fit in a technically demanding environment. However, the lack of professional experience or team-based projects limits the assessment of collaboration and broader workplace cultural fit.
Soft Skills & Operational Fit
The candidate's project descriptions suggest a methodical approach to problem-solving and an ability to articulate technical solutions. The focus on deploying models and optimizing performance indicates an operational mindset. However, without direct interaction or psychometric test results, a comprehensive assessment of soft skills like teamwork, leadership, or adaptability is not possible.