Sarvesh Sirmukaddam

Product Manager

Bengaluru, Karnataka, India6 yrs experience

Highly StableAI ML Practitioner

Key Highlights

Led growth initiatives achieving 30M+ MAU.
Developed AI-driven personalization for educators.
Implemented machine learning solutions reducing costs.

Stackforce AI infers this person is a Product Manager with expertise in EdTech and Fintech, focusing on AI and data-driven solutions.

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Skills

Core Skills

Product ManagementProduct StrategyMachine LearningData AnalysisR&d

Other Skills

A/B TestingA/B testingAI-powered personalizationAgile DevelopmentAnalytical SkillsAnalyticsAndroid DevelopmentBusiness AnalysisBusiness InsightsBusiness RequirementsC++CommunicationCompetitive AnalysisComputer VisionCross-functional Team Leadership

About

Problem-solving enthusiast driven by a desire to use the transformative power of technology for meaningful change, influencing user habits and business evolution. With a commitment to comprehensive end-to-end execution, my approach is rooted in effective cross-functional team coordination and a deep commitment to developing forward-thinking product visions.

Experience

6 yrs

Total Experience

2 yrs 6 mos

Average Tenure

1 yr

Current Experience

Wayground (formerly quizizz)

Product Manager

Jun 2025 – Present · 1 yr

Search , Discovery and Personalisation
Building AI-powered personalization, search (algorithms + UX), and storefront (browse + homepage) experiences that guide millions of educators to the right content. These discovery journeys and in-product funnels drive acquisition, engagement , and long-term retention.

AI-powered personalizationsearch algorithmsuser experienceProduct ManagementProduct Strategy

Sharechat

Product Manager

Apr 2021 – Jun 2025 · 4 yrs 2 mos

Led various charters in the 0-1 and 1-10 journey of the Live Platform from ideation to 30M+ MAU , 250K+ Monthly Paying Users and $65Million+ ARR.
Growth → Drove 2.5x increase in daily spenders and 1.2x ARPU through rapid experimentation, loyalty programs, and gamification. Scaled a 1:1 Creator-to-Fan calling product to ₹1Cr+ MRR in 3 months with 62% D7 retention.
Explore Section for Livestreams → Enhanced content discovery by redesigning the UI, improving session duration by 30%, click-through rates by 12%, and discoverability by 18% with AI-powered trending and interactive elements.
New User Acquisition & Experience → Scaled daily live viewers from 0.8M to 4M, increased engagement 3x through UI optimizations, and improved retention by 23% with A/B-tested feed logic for first-time users.
Streaming Platform → Cut streaming costs by 30% through vendor migration and ML-driven RTC/HLS switching. Reduced live loading times by 70%, improving retention and time spent.
Supply Management Platform & Creator Tools → Increased monthly earning creators by 20% and boosted gifting revenue 2.3x with community monetization tools like battles and leaderboards. Improved creator retention by 5% with lifecycle management tools.

A/B testingUI optimizationgamificationdata-driven insightsProduct ManagementProduct Strategy

Hsbc

ML Engineer, HSBC

Jun 2020 – Apr 2021 · 10 mos · Pune, Maharashtra, India

Part of the Global Graduate Program (Tech) , attached to the Emerging Technologies group in the Wealth & Personal Banking Team.
1) Designed and deployed a content-based stock recommender system using auto-encoders to model portfolio preferences, reducing analyst research load and aligning with portfolio managers' investment styles.
2) Implemented K-means clustering on learned manifolds to identify and recommend potential stocks, expanding the investment universe by 15x while reducing processing time to 1/12th compared to traditional manual research methods.
3) Enhanced decision-making with automated interactive visualizations and detailed reports, improving stakeholder trust and usability.

machine learningK-means clusteringdata visualizationMachine LearningData Analysis

Samsung r&d institute india

R&D Intern

Jan 2020 – Jun 2020 · 5 mos · Bengaluru, Karnataka, India

Camera Systems R&D
Developed an optical flow segmentation inspired Intelligent Frame Rate Selection for Super Slow-Motion recordings for flagship Samsung smartphones to improve User Experience.
Increasing user approval rating by 30% points.

optical flow segmentationuser experienceR&D

Fidelity investments

Intern – Emerging Technologies Group

Jul 2019 – Dec 2019 · 5 mos · Bengaluru, Karnataka, India

Developed predictive models to forecast mutual fund inflows and outflows using Python, SQL, and machine learning libraries (Scikit-learn, TensorFlow), leveraging historical data, macroeconomic indicators, and investor sentiment analysis.
Streamlined data processing workflows by integrating APIs for real-time market data and automating ETL pipelines with Apache Airflow, improving data accuracy and reducing processing time by 20%.
Enhanced fund liquidity management strategies, enabling portfolio managers to anticipate cash needs and reduce forced asset sales, contributing to a 15% improvement in operational efficiency.

predictive modelingdata processingETL pipelinesData Analysis