Mukund Aggarwal

Operations Associate

Noida, Uttar Pradesh, India11 mos experience

Most Likely To Switch

Key Highlights

Expertise in Bayesian learning and scalable ML engineering.
Successful internships at Google with impactful projects.
Strong mentoring and teaching experience in advanced statistical methods.

Stackforce AI infers this person is a skilled AI/ML engineer with a focus on scalable solutions and advanced statistical methods.

Contact

Skills

Core Skills

StatisticsProbabilityComputer VisionNatural Language Processing (nlp)Research Skills

Other Skills

Statistical ModelingProbability TheoryStochastic ProcessesOpenCVTensorFlowC++Large Language Models (LLM)Apache BeamSQLPythonData AnalysisSeleniumData ScrapingJAXNumPyro

About

Engineer and researcher at the intersection of Bayesian learning and scalable ML engineering. Interned twice at Google, building production pipelines across NLP and Computer Vision.

Experience

11 mos

Total Experience

11 mos

Average Tenure

11 mos

Current Experience

Indian institute of technology, delhi

2 roles

Head Teaching Assistant

Promoted

Jan 2026 – Present · 5 mos · New Delhi, Delhi, India

• Head TA for the course MTL390: Statistical Methods.

StatisticsStatistical Modeling

Teaching Assistant

Jul 2025 – Jan 2026 · 6 mos · New Delhi, Delhi, India

TA for the course MTL106: Intro. to Probability & Stochastic Processes.
Mentored 50 students weekly via tutorials; designed new problem sets for important concepts.
Managed grading for 250 exams, delivering constructive feedback.

Probability TheoryStochastic ProcessesProbability

Google

2 roles

Software Engineering Intern

May 2025 – Jul 2025 · 2 mos · Hyderabad, Telangana, India

Architected a video stream occlusion detection system integrating image quality assessment, object detection, and depth estimation using PaliGemma2 for multimodal inference; contributed enhancements to Gemma.cpp open-source repository.
Engineered TensorFlow ML models in C++ gated via Gradient Boosted Decision Trees, achieving 71% accuracy, 71% precision, and 96% recall — significantly outperforming in-house baseline on proprietary Unity dataset.
Orchestrated end-to-end development lifecycle from data modelling and unit testing with dependency injection to integration into a scalable, production-grade graph processor.
Secured a full-time offer for outstanding technical performance and project delivery.

Computer VisionOpenCVTensorFlowC++

Software Engineering Intern

May 2024 – Jul 2024 · 2 mos · Bengaluru, Karnataka, India

Designed LLM pipeline for IAM Entitlement Prediction leveraging Gemini API embeddings and engineering a custom Transformer architecture.
Constructed an online data processing pipeline in Apache Beam, SQL, and Python for ingesting GCP and AWS audit logs at scale.
Attained 85% accuracy, 94% precision, and 83% recall; presented a complete system to senior leadership.
Secured a return internship offer based on exceptional performance and project delivery.

Natural Language Processing (NLP)Large Language Models (LLM)Apache BeamSQLPython

University of sydney

Research Intern

May 2023 – Jul 2023 · 2 mos · Sydney, New South Wales, Australia

Supervised and guided by Prof. Uwe Roehm from the School of Computer Science.
Researched deep reinforcement learning enhancements for MongoDB's FPTP optimiser.
Developed profiling experiments for measuring resource utilisation and optimising system performance.
Executed statistical analysis and visualisation of real-world data.

Research SkillsData Analysis

Grant thornton bharat llp

Summer Trainee

Dec 2022 – Jan 2023 · 1 mo · Gurugram, Haryana, India · Remote

Built a robust Selenium web scraping and data aggregation app to bypass bot restriction mechanisms.
Implemented ticker extraction functionality from live charts and graphs.
Crafted an intuitive user interface via TKinter.

SeleniumData Scraping