Goutham

I am an Application Engineer with a strong academic foundation in Computer Science and Engineering from IIT Mandi and hands-on industry experience in AI-driven solutions, large language models (LLMs), and enterprise automation platforms. My career is centered on building intelligent systems that enhance efficiency, streamline workflows, and create meaningful impact for organizations.

Currently, I work at EMA Unlimited, Inc. as a Solution Application Engineer, where I lead the end-to-end implementation of Generative AI solutions for Fortune 500 clients. My responsibilities span requirements gathering, LLM prompt engineering, system integration, and deployment of the EMA Employee platform. I have successfully developed and deployed multiple proof-of-concepts (PoCs) that showcase EMA’s capabilities in customer support automation and business process optimization. A notable achievement includes architecting automation workflows to seamlessly integrate EMA with client systems, ensuring smooth adoption and measurable business outcomes.

Previously, I interned at Siemens Technology and Services, where I engineered a Reference Analyzer tool that improved build times of C# projects by 46%. I leveraged Roslyn APIs, Reflection, and .csproj parsing to analyze dependencies and created interactive visualization dashboards with d3.js for better insights. This experience solidified my expertise in **software optimization, systems-level development, and visual data representation.

In addition to professional experience, I have contributed to multiple research-oriented and applied projects. At the Yamaha Hackathon, I built VineNet, a U-Net deep learning model for grape bunch segmentation in vineyard images, achieving high precision and recall. I also developed a CT Scan Reconstruction pipeline using GANs and U-Net with CNCL strategies, significantly improving denoising for DICOM datasets. Another highlight is HybridQC, a quantum convolutional neural network (QCNN) for image classification, which achieved 98% accuracy using amplitude embedding and variational quantum circuits.

My technical toolkit includes C++, C#, Python, Java, SQL, TensorFlow, PyTorch, Keras, LLMs, Roslyn APIs, and automation tools like Workato. I am also proficient in database management (MySQL, MongoDB, PostgreSQL) and visualization (d3.js), with strong knowledge in operating systems, data structures, and machine learning.

I thrive in fast-paced, collaborative environments, where I can translate complex technical concepts into practical solutions. With a balance of research experience, software engineering expertise, and client-focused delivery, I aim to continue building impactful AI systems that solve real-world challenges and drive business transformation.