Shivank Goel

I am a Machine Learning–oriented Engineer with experience designing and deploying AI-enabled, data-driven systems focused on performance, scalability, and real-world impact. My work emphasizes applying machine learning and AI techniques in production, supported by reliable backend systems and efficient data pipelines.

During my internships, I applied data-driven optimization and automation to improve system performance, including migrating an e-commerce platform (https://amala.earth) to Next.js, achieving a 45% improvement in page load speed and a 22% reduction in bounce rate. I also developed MentorLink (https://sdcmuj.com), a mentorship platform serving 200+ users, where I improved server latency by 25% and implemented AI-assisted mentor–mentee matching and recommendation logic to enhance engagement and pairing quality.

I also built TranscendentalTLS (https://transcendentaltls.com/), an AI-powered web platform that automatically crawls public-domain books from multiple online sources, processes and structures the content, and uses NLP-based machine translation models to translate and present books to users. This project involved automated data ingestion, text preprocessing, translation workflows, and scalable content delivery, demonstrating my ability to build end-to-end AI pipelines from data collection to user-facing deployment.

I have hands-on experience integrating AI models, intelligent automation, and recommendation systems into production applications, deploying them with Node.js, MongoDB, and cloud platforms such as Vercel. My work bridges machine learning concepts and production engineering, ensuring AI solutions are robust, scalable, and maintainable.

I bring strong skills in problem-solving, AI system design, backend integration, and deployment, along with collaborative communication and attention to detail. I am seeking opportunities to design, deploy, and scale AI- and ML-driven systems that deliver measurable improvements in performance and user experience within high-quality engineering teams.