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Clinton KJ

Clinton KJ

Reach me at +91-8589852956

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Experience

Gilbert Research Center                                         08-2023  -  09-2023
Intern (Data Science and Machine Learning)

As a research intern, I fine-tuned convolutional neural networks (CNNs) in PyTorch, resulting in a 15% boost in image classification accuracy. I applied data augmentation techniques and convolution-based denoising to improve feature extraction. Additionally, I reduced preprocessing time by 30% through batch optimization and signal filtering, contributing to more efficient model training workflows.
AI/ML Engineer (Contract)                                         02-2023 - 07-2023
Graduate Engineer Trainee

At Startup Writer, I developed an AI-powered cold email automation platform using OpenAI's LLMs and advanced prompt engineering. I integrated OpenAI APIs directly into the frontend to generate personalized content and managed the full stack, including a Flask/Node.js backend and Angular frontend. I contributed actively to product planning and MVP delivery for the early customer rollout phase. My optimization work improved API throughput and scalability, ensuring the platform could handle high-volume campaigns efficiently.
Siemens Technology and Services                                  12-2021 - 01-2023
Graduate Engineer Trainee

During my time at Siemens, I built predictive models for transformer maintenance, significantly reducing operational downtime. I used Python and SQL for data engineering and began exploring PySpark to handle larger datasets. I also enhanced the performance of internal applications by 40% and maintained code quality standards above 87%, monitored via SonarQube.
Tata Consultancy Services                                         04-2021 - 10-2021
Assistant System Engineer Trainee

At TCS, I automated several internal workflows using Power Automate, which reduced manual effort by over 60%. I migrated legacy systems to the Microsoft Power Platform and contributed to CI/CD pipeline implementation, cutting deployment time by nearly 30%. These efforts helped modernize internal tools and improve scalability across departments.