Nandini Jaryal

Software Engineer at Samsung R&D Institute Bangalore

Software Engineer in the Context Intelligence Team. Built and optimized context-aware data pipelines and APIs for flagship devices; contributed to on-device intelligence improvements; developed GenAI tooling for bug detection; authored system diagrams and docs; contributed to invention disclosures and patent filings for Galaxy AI.

Software Engineer at Samsung R&D Institute Bangalore

Context Intelligence Team: Building Samsung’s Personal Data Engine for context-aware intelligence on next-gen flagship devices. Develop framework-level APIs and SDKs to enable context-aware services for enterprise-scale applications. Built and optimized scalable data pipelines and integration layers with SQL databases, improving processing efficiency by 60%. Implement algorithmic enhancements to reduce time complexity, compute cost, and memory usage for on-device intelligence. Contribute to pre-release R&D, working on invention disclosures, patent filings, and innovation cycles for Galaxy AI. Built internal GenAI tools using Samsung LLMs and RAG workflows to automate bug detection and testing for customers and field engineers. Author and maintain technical docs and system diagrams for engineering and product alignment, and product iteration.

Software Engineer at Samsung R&D Institute Bangalore, India

Context Intelligence Team: Building Samsung's Personal Data Engine for context-aware intelligence on next-gen flagship devices. Develop framework-level APIs and SDKs enabling context-aware services for enterprise-scale applications. Built and optimized scalable data pipelines and integration layers with SQL databases, improving processing efficiency by 60%. Implemented algorithmic enhancements to reduce time complexity, compute cost, and memory usage for on-device intelligence. Contributed to pre-release R&D, working on invention disclosures, patent filings, and innovation cycles for Galaxy AI. Built internal GenAI tools using Samsung LLMs and RAG workflows to automate bug detection and testing for customers and field engineers. Authored and maintained technical docs and system diagrams for engineering and product alignment and iteration.

Software Engineer at Samsung R&D Institute Bangalore

Building Samsung's Personal Data Engine for context-aware intelligence on next-gen flagship devices. Develop framework-level APIs and SDKs enabling context-aware services for enterprise-scale applications. Built and optimized scalable data pipelines and integration layers with SQL databases, improving processing efficiency by 60%. Implement algorithmic enhancements to reduce time complexity, compute cost, and memory usage for on-device intelligence. Contribute to pre-release R&D, invention disclosures, patent filings, and innovation cycles for Galaxy AI. Built internal GenAI tools using Samsung LLMs and RAG workflows to automate bug detection and testing for customers and field engineers. Author and maintain technical docs and system diagrams for engineering and product alignment, and product iteration.

Software Engineer Intern at Samsung R&D Institute Bangalore

Automated log analysis using Python, Bash, and Linux tools; improved C++/Python performance by 30%; designed CI/CD pipelines with GitHub Actions; optimized data structures and algorithms; contributed to code reviews.

Software Engineer Intern at Samsung R&D Institute Bangalore

Automated log file analysis using Python, Bash, and Linux tools; refactored C++/Python code to improve performance by 30%. Designed and implemented CI/CD pipelines using GitHub Actions, streamlining build, test, and deployment processes for faster and more reliable releases. Optimized data structures and algorithms, boosting error analysis efficiency by 60%; contributed to code reviews and provided actionable feedback.

Software Engineer Intern at Samsung R&D Institute Bangalore, India

Automated log file analysis using Python, Bash, and Linux tools; refactored C++/Python code to improve performance by 30%. Designed and implemented CI/CD pipelines using GitHub Actions, streamlining build, test, and deployment processes for faster and more reliable releases. Optimized data structures and algorithms, boosting error analysis efficiency by 60%; contributed to code reviews and provided actionable feedback.