Nicholas Goh
AI/ML Software Engineer
Software engineer with a passion for AI and intelligent systems. I've built everything from enterprise AI chatbots to surgical robotics interfaces, always focusing on creating impactful solutions that make a real difference.
Get in TouchWork Experience
Hewlett-Packard Enterprise
AI/ML Software Engineering Intern
May 2025 — Aug. 2025- Architected and deployed GraphRAG-powered AI chatbot combining a Neo4j graph database, vector embeddings, and full-text search with Docker containerization, enhancing retrieval accuracy by 40-60% and reducing manual QA test generation time by 30-50%.
- Built an enterprise-scalable RAG framework with secure internal API integration, advanced PDF processing for context preservation, and persistent document repository that enables automated test case generation and knowledge sharing across multiple engineering teams.
- Transformed siloed technical documentation into an AI-accessible knowledge management system that replaces legacy LLM wrappers, accelerates information access across engineering/sales organizations, and establishes a scalable technical foundation for enterprise-wide AI automation initiatives.
Stryker
Software Engineering Intern
May 2024 — Aug. 2024- Engineered an intuitive graphical user interface (GUI) tool for a surgical robotics system using C++ and the Qt framework; implemented real-time visual force feedback, improving surgical accuracy by up to 80%.
- Leveraged Python and Pandas to conduct comprehensive data analysis; processed over 10,000 data points to optimize the Qt-based interface and notably improve system response time.
- Led a pivotal proof-of-concept research project; successfully demonstrated the feasibility of integrating advanced force feedback functionality into existing software, accelerating feature development.
Stryker
Software Engineering Intern
May 2023 — Nov. 2023- Implemented Gherkin-based unit testing in Python and resolved dozens of CI failures, increasing test coverage and maintaining >95% codebase integrity.
- Developed custom Bash scripts to streamline customer deployment and modernized software features in Ruby.
- Orchestrated project workflows and team collaboration using Jira and Bitbucket within an Agile/Scrum framework enhancing productivity and meeting sprint goals.
Boeing
Data Engineering Intern
May 2022 — May 2023- Wrote and deployed Python automation scripts, transforming manual spreadsheet inputs into standardized database tables that reduced data entry time by approximately 50%.
- Analyzed 10M+ record datasets using complex Oracle and Teradata queries, delivering insights that enhanced operational efficiency across multiple aircraft programs and improved resource allocation for enterprise-scale engineering teams.
- Designed and deployed two comprehensive Tableau dashboards for executives, increasing the number of key performance indicators by 40% and contributing to an improvement in talent retention rates.
Featured Projects
About Me
Hi, I'm Nicholas Goh, a Software Engineer specializing in AI/ML systems and full-stack development with experience building GraphRAG chatbots, surgical robotics GUIs, and enterprise data solutions. I'm passionate about leveraging cutting-edge technology to solve complex engineering challenges that make a real-world impact. Throughout my internships at Fortune 500 companies like HPE, Stryker, and Boeing, I've developed a strong foundation in both traditional software engineering and emerging AI technologies. From architecting enterprise-scale RAG frameworks that improved retrieval accuracy by 40-60% to engineering intuitive surgical robotics interfaces that enhanced accuracy by 80%, I thrive at the intersection of innovation and practical application. My projects span the full spectrum of modern software development—from computer vision systems achieving >95% accuracy on edge computing platforms to full-stack AI applications that won 2nd place at hackathons. I focus on building robust, scalable solutions that not only meet technical requirements but also drive measurable business outcomes and user satisfaction.
