Hyperbound

Co-Founder & CTO/CRO

RevGenius

Member

Sales Enablement Collective

Ads Machine Learning Engineer

Carnegie Mellon University

Built classifier for large scale ICD-10 code Ranking and Classification for ER admissions
Modularized classification and metric architecture for faster development iteration

Machine Learning Researcher

Implemented Meta-wide multimodal contrastive loss classifier based on recent research
Engineered several features with 6-point gain for Creator Classification and Segmentation 
Developed self-supervised user embeddings to improve segmentation generalization

Machine Learning Intern

Facebook

Trained ML models to capture complex relationship between hyperparameters and
notification metrics
Utilized candidate generation, ranking, and filtering to suggest optimal hyperparameters
Achieved tentative metric wins in unwanted notification volume and comments

Utilizing dependency parsing (NLP) to extract technical information from patents
My latest CNN model identifies software patent claims with 93%+ accuracy
Publishing research on various NLP and ML based classifiers this year

ML/NLP Researcher

Amazon

Developed transfer learning strategies to improve search results, widgets, and ads in more than 6 marketplaces
Engineered machine learning features from combinations of search query data in several locales
Productionized flexible cloud infrastructure for massive language model development

Software Development Engineering Intern

Lockheed Martin

Implemented chaos engineering with Gremlin to improve security and stability of cloud deployments
Integrated container automation and validation software in Docker-In-Docker sandbox on AWS GovCloud
Led team using Agile methodologies to develop highly-available cloud infrastructure as code on AWS

Software Engineering Intern

Founder and CRO at Hyperbound (YC S23) | AI Sales Roleplay

CTO and CRO here @ Hyperbound. We're a YCombinator startup building the next generation of AI GTM.

I’ve been quiet for a reason.

The last few months at Hyperbound have been about building foundations that will keep us years ahead of the pack. New structures, new processes, new hires.

We started this year with 9 people.
We’re ending it with 30.

And one of the two most important hires in that growth is our new Chief of Staff, Mason Smith.

We’ve worked with Mason since the start of this year. He’s the one who quietly pulled a massive workload behind the scenes to get us ready for our fundraise while he was still at Parallel.

Mason’s work ethic and attitude are the perfect example of what we look for in Hyperbound’s culture: Hard working, confident, low ego, obsessed with outcomes, and unshakably reliable.

The kind of person you want in the trenches with you when the stakes are high.

Welcome officially, Mason. Excited for what’s next.

P.S. Check out latest Hyperbound capabilities: https://bit.ly/4raaUUO

Atul Raghunathan

Hyperbound just dropped one of our coolest features of the year… again.

The Hyperbound Chrome Extension is live!

It lets you build an AI roleplay bot directly from a LinkedIn profile - turning public prospect data into a realistic, one-click roleplay scenarios.

This matters because it bridges a gap most teams don’t realize they have:

Reps spend hours researching prospects, but that context rarely makes it into their training.

They learn one way, sell another and the two never meet.

Now, they can take the exact context they sell in every day and use it to practice the conversation before it happens.

No setup. No templates.

Just open a LinkedIn profile, click the Hyperbound icon, and build a practice scenario grounded in real buyer context.

It’s a major differentiator because it makes training continuous.

Reps don’t have to leave their workflow to learn.

They can practice, improve, and personalize in the same place they're already prospecting.

The Chrome Extension takes that one step further - bringing true buyer context into every rep’s daily routine.

Hyperbound Chrome Extension.

🔗 https://lnkd.in/e_mE4ttD

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