Python Engineer with less than a year in Python, Django, and computer vision, seeking an entry-level
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Computer Science Engineering graduate with hands-on experience in Manufacturing Execution Systems (MES) and computer vision. Skilled in Python, YOLO, OpenCV, and SQL, with experience in real-time object detection and production counting. Seeking an entry-level role in software, automation, or manufacturing IT.
Jain College of Engineering and Technology
Bachelor of Engineering · Computer Science and Engineering
June 1, 2020 – May 1, 2024
Haegl Technologies PVT Ltd
Full-Stack Developer
September 1, 2023 – October 1, 2023
India
Manufacturing Execution System (MES)
September 1, 2025 – Present
• Designed and implemented a real-time Manufacturing Execution System (MES) to automate production counting. • Trained a YOLO-based object detection model to identify and classify multiple pan varieties. • Integrated Intel RealSense depth camera for accurate object detection and movement-based counting. • Developed logic to handle double counting, missed detections, and cooldown timing to improve counting accuracy. • Reduced dependency on manual counting and improved reliability of production data.
View ProjectCultural Fit Analysis
The candidate's academic project on MES and internship as a Full-Stack Developer show a blend of practical application and foundational development skills. The involvement in student activities and community support suggests a collaborative and socially conscious individual. The target role of 'Python Engineer' aligns well with the candidate's primary technical skills and project experience, indicating a good cultural fit for a role focused on Python development and potentially computer vision applications.
Soft Skills & Operational Fit
The candidate's resume highlights participation in student associations and AICTE activities, suggesting an ability to collaborate and engage in community. The description 'Quick learner with strong problem-solving and analytical skills' indicates a positive attitude towards challenges and continuous improvement. The MES project demonstrates problem-solving in handling edge cases like double counting and missed detections.