Ruturaj Kalmegh
Associate Quality Assurance Engineer @Jio Platforms Limited Jpl
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WORK HISTORY
Associate Quality Assurance Engineer @Jio Platforms Limited Jpl
Navi Mumbai, IN
Executed 1,500+ test cases across STB platforms, OTT applications (JioTV+, YouTube, Prime Video), XR apps (JioImmerse), and firmware features, achieving 98% test coverage in pre-production cycles.Identified and reported 250+ high-severity defects (Blocker/Critical), improving release stability by 30% and significantly reducing customer-facing issues during pilot launches.Implemented severity-based defect reporting, improving triage accuracy by 40% and accelerating root-cause analysis, resulting in faster defect resolution.Performed large-scale content validation for media assets, ensuring a high-quality and seamless user experience across OTT platforms.Developed an Automated Productivity Reporting system using Python (Pandas, NumPy), reducing manual reporting effort by 25% and enabling data-driven tracking of testing efficiency.Leveraged AI tools in QA workflows, including building an AI Comic Generator and contributing to defect pattern analysis models, improving test prioritization and reducing regression cycle time by 30%.
EDUCATION
Udacity
NANODEGREE,AI PROGRAMMING WITH PYTHON
Datta Meghe College of Engineering CIDCO Sector III Airoli Navi Mumbai 400 708
Bachelor of Engineering - BE, Electrical and Electronics Engineering
Datta Meghe College of Engineering
Bachelor of Engineering - BE, Electronics Engineering
ABOUT RUTURAJ KALMEGH
I am an AI/ML & QA Engineer with hands-on experience in pre-production testing, automation, and data-driven quality assurance at Jio Platforms Ltd.I specialize in bridging the gap between traditional software testing and applied AI, leveraging Python, Machine Learning, and Data Analysis to improve product quality, optimize testing workflows, and drive intelligent automation.At Jio, I have contributed to large-scale testing across OTT, STB, and XR platforms, while also building automation solutions and AI-driven systems to enhance efficiency and defect detection. Key Skills: Python • Machine Learning • Data Analysis • Automation • Prompt Engineering • QA Testing • AWS Cloud • Power BI AWS AI & ML Scholar (2022) Key Contributions: Built automated QA productivity reporting systems using Python (Pandas, NumPy) Developed AI-driven solutions such as an AI Comic Generator and defect pattern analysis models Improved test prioritization and reduced regression cycle time using data-driven approaches Current Focus:Exploring AI-driven test automation, MLOps in QA environments, and real-world applications of Generative AI in product quality assurance. Open to opportunities, collaborations, and discussions in AI-driven QA, Data Analytics, and Product Quality Engineering.
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