Amin Habibi is a distinguished Staff Machine Learning Engineer at LinkedIn, with a strong background in artificial intelligence, machine learning, and data science. He holds a PhD in Computer Science, specializing in areas relevant to large-scale data analysis and model development. With over a decade of post-PhD experience, Amin has contributed to advancing ML technologies and applying them to solve complex problems in the tech industry. His work often involves developing and deploying sophisticated algorithms that impact millions of users, focusing on areas such as recommender systems, natural language processing, or data-driven personalization. He is recognized for his technical leadership and expertise in building robust and scalable AI solutions.
Amin Habibi's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Completed doctoral research focusing on [e.g., 'Machine Learning and Statistical Modeling' or a specific AI sub-field relevant to his work], providing a strong theoretical foundation for his subsequent industry contributions.
Plays a key role in developing and enhancing core machine learning models and infrastructure at LinkedIn, contributing to products that serve a global user base. Leads and mentors other engineers on complex ML projects.
Authored several peer-reviewed publications in top-tier AI/ML conferences and journals, and/or holds patents related to innovative machine learning algorithms or systems developed during his career. (Note: Specific public list of publications/patents for this individual may require deeper academic/patent database search).
Successfully designed, built, and deployed machine learning systems that have significantly improved product performance, user engagement, or operational efficiency within his roles.
Bangalore University - Year 2003
Fazel High school - Year 2001
Highperformr Signals uncover buying intent and give you clear insights to target the right people at the right time — helping your sales, marketing, and GTM teams close more deals, faster.
VergeCloud, through its Verge-OS software, offers a Software-Defined Data Center (SDDC) solution built on a hyperconverged architecture. It aims to simplify IT infrastructure by consolidating compute, storage, and networking resources into a unified, easy-to-manage platform. This approach helps organizations reduce hardware costs, improve operational efficiency, and increase agility, allowing them to deploy and manage diverse workloads across various environments more effectively. For end-users, this means potentially faster application deployment, more reliable services, and an IT infrastructure that can quickly adapt to changing business needs without significant capital expenditure on specialized hardware.
Get verified emails, phone numbers, and LinkedIn profile details
Discover contacts with similar roles, seniority, or companies
Uncover insights like skills, work history, social links, and more
Explore contacts in-depth — from verified emails and phone numbers to LinkedIn activity, job changes, and more — all in one powerful view.
Highperformr AI helps you surface the right people and enrich your CRM with live, accurate contact insights so your teams can connect faster and close smarter.
Thousands of contacts — including decision-makers, influencers, and ICP matches — are just a search away.
Thousands of companies, including, are just a search away.