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AI Engineer with less than a year in Machine Learning & Deep Learning
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Highly motivated and detail-oriented AI Engineer with 3 months of hands-on experience as a Machine Learning Intern and a strong academic background in Computer Science & Engineering. Proven ability to develop and deploy machine learning and deep learning models for complex prediction and classification tasks, as demonstrated through undergraduate thesis and personal projects. Eager to apply strong Python programming skills, MLOps basics, and a deep understanding of AI/ML concepts to innovative challenges.
East Delta University
Bachelor of Science · Computer Science & Engineering
August 1, 2022 – June 30, 2026
Amader Bashundhara
Machine Learning Intern
April 1, 2026 – June 30, 2026
India
Osteoporosis Risk Prediction (Undergraduate Thesis)
June 1, 2026 – June 1, 2026
• Developed and compared ML and CNN models for osteoporosis prediction using knee X-ray and lifestyle data, achieving up to 0.94 ROC-AUC • Applied explainable AI techniques (Grad-CAM, SHAP) to interpret model decisions and identify key predictive features • Analyzed trade-offs between interpretability and performance in medical prediction
Skin Cancer Detection using CNN
June 1, 2026 – June 1, 2026
• Built and trained a CNN model to classify melanoma from skin lesion images, achieving 92% accuracy • Improved model performance through image preprocessing and data augmentation techniques
Cultural Fit Analysis
The candidate's academic projects show a strong interest in applying AI to impactful domains like healthcare, which aligns with a problem-solving and innovation-driven culture. The internship experience, though brief, indicates an ability to contribute to practical applications. The high academic achievement and scholarship suggest diligence and a strong work ethic. However, the limited professional experience and lack of diverse project types beyond academic settings make a deep assessment of cultural fit challenging without further interaction.
Soft Skills & Operational Fit
The candidate's resume indicates a structured approach to problem-solving through iterative testing and evaluation in project descriptions. The academic projects demonstrate initiative and the ability to work on complex, self-directed tasks. However, without psychometric test results or interview data, a comprehensive assessment of soft skills like teamwork, stress handling, and communication clarity in a professional setting is not possible.