Ankur Aggarwal

Senior Software Engineer

San Francisco, California, United States14 yrs 4 mos experience

Highly Stable

Key Highlights

Pioneered Generative AI technologies at Meta.
Launched AI-driven recommendation infrastructure at Google.
Trained state-of-the-art neural networks for biomedical applications.

Stackforce AI infers this person is a Full-Stack Software Engineer specializing in AI and Data Science across SaaS and Automotive industries.

Contact

Skills

Core Skills

Applied Machine LearningRecommender SystemsDeep LearningNatural Language Processing (nlp)Software DevelopmentData Mining

Other Skills

Cross-functional Team LeadershipAndroidData SciencePythonKaffkaApache SparkMapReduceCassandraScala in SparkPython (Programming Language)C++CData AnalysisAlgorithmsData Structures

About

I'm a full-stack Software Engineer with a strong background in applying statistics and machine learning to create impactful user-facing products and features. I have a proven track record delivering AI-powered innovative products and services that have had a significant impact on user experience and engagement At Meta, my focus is on pioneering Generative AI technologies to build novel solutions that enrich user interactions. At Google, I successfully co-founded and launched an AI driven recommendation infrastructure that lifted Assistant penetration by 11% across 50 million automobiles worldwide. Prior to Google, I have trained and deployed deep neural networks for Named Entity Recognition in biomedical journals and built a metrics monitoring pipeline for 2 million DAU using a Lambda architecture.

Experience

14 yrs 4 mos

Total Experience

2 yrs 6 mos

Average Tenure

1 yr 5 mos

Current Experience

Google

Senior Software Engineer

Apr 2018 – Oct 2024 · 6 yrs 6 mos · Mountain View, California, United States · Hybrid

[Google Analytics] Led the successful launch of the LLM powered chatbot for Google Analytics enabling users to interactively get answers to their data queries.
[Google Assistant] Led the engineering strategy, execution and launch of x-surface multimodal proactive and personalized feature recommendation infrastructure that contributed to an overall +11% Assistant Penetration lift across 50 million Monthly active cars(48 M using Android Auto Projected and 2M using Android Auto Embedded)
Led a cross-functional team (UX, PM, PEng, BD) to integrate the recommendation infrastructure across diverse OEM infotainment systems (GM, Volvo, Renault, Honda), strengthening Google Assistant’s strategic value in a $1B partnership (2 patent pending + 2 defensive publication)
Spearheaded a data-driven strategic understanding of the product funnel, user lifecycle, user segments and drivers of user retention which laid the foundations of the multi-year product growth strategy (1 patent pending)

Recommender SystemsApplied Machine LearningCross-functional Team LeadershipAndroidData Science

Chan zuckerberg initiative

Research Science Intern

Jun 2017 – Aug 2017 · 2 mos · Palo Alto, California · On-site

Trained BiLSTM-CRF based neural network models using Tensorflow in Python achieving state-of-the- art F1 scores in academic research.
Deployed the model in production for automated population of scientific knowledge graphs.

Deep LearningApplied Machine LearningSoftware DevelopmentPythonNatural Language Processing (NLP)

Airtel

Senior Software Engineer

Jan 2015 – Aug 2016 · 1 yr 7 mos · Gurgaon · On-site

Single-handedly designed, implemented and launched a metrics monitoring pipeline for around 2 million DAU (15M user events/ day) using the Lambda architecture
Supported complex user segmentation and near-to-real time campaign notification analysis thereby enabling the product management team to launch multiple campaigns that increased the monthly active users(MAU) of top three mobile applications by 15%

Software DevelopmentKaffkaApache SparkMapReduceCassandraScala in Spark+1

Guavus inc

Analytics Engineer

Apr 2013 – Dec 2014 · 1 yr 8 mos · Gurgaon, India · On-site

Designed and developed a web page categorization engine in Python which categorized around 1.6 million web pages into 24 Tier1 and 360 Tier2 categories of Interactive Advertising Bureau(IAB) with an overall accuracy of around 78% validated by a third party.

Applied Machine LearningSoftware DevelopmentApache SparkPython (Programming Language)