Artificial Intelligence employees at Intel have the unique opportunity to apply their expertise in creating solutions that span the entire Artificial Intelligence Stack—from frameworks, algorithms, and research to Artificial Intelligence business, SoC, and designing Artificial Intelligence-specific silicon.
Our approach is holistic, and our employees collaborate and learn from other world class peers in adjoining fields, and academia, creating open platforms and real-world solutions that are already impacting our society in uplifting and meaningful ways.
Our approach is holistic, and our employees collaborate and learn from other world class peers in adjoining fields, and academia, creating open platforms and real-world solutions that are already impacting our society in uplifting and meaningful ways.
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Right hereOur variety of AI teams have a common passion for innovation, driving new technologies that solve real-world challenges across the globe.
As Artificial Intelligence represents one of the most critical growth areas for the company, we have an extensive range of opportunities to offer in different domains. Take a look for yourself, this is what we do, and we’re extremely proud of it!
The AI Lab team consists of experts in machine learning, deep learning, data science, and neuroscience. Our academic collaborations keep us on the cutting-edge of research in the field of AI and our industrial partners enable us to discover how to apply AI to real-world problems.
In 2012 and 2018, Intel Chengdu was honored with the Intel Quality Award for its outstanding business contributions and organizational excellence. The site is known for its strong “Chengdu Can Do” culture and is a source of pride for Intel, our local communities, and our families.
Reinforcement Learning Coach is an open source research framework for training and evaluating reinforcement learning (RL) agents, using the processing power of multi-core CPUs to enable efficient training of RL agents.
Learn moreIntel’s AI Lab is working to solve one of the toughest problems in deep learning today. Inspired by biology, BRAINet is a principled, theoretically grounded approach to learning neural network topologies in an unsupervised manner. These topologies are compact and robust and deliver high quality results on various computer vision datasets.
Learn moreNetwork compression can reduce the memory footprint of a neural network, increase its inference speed, and save energy. Distiller provides a PyTorch environment for prototyping and analyzing compression algorithms, such as sparsity-inducing methods and low-precision arithmetic.
Learn moreNLP Architect is an open-source Python library for exploring the state-of-the-art deep learning topologies and techniques for natural language processing and natural language understanding. It is intended to be a platform for future research and collaboration.
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Intel’s Advanced Analytics solves the company’s global challenges using AI, while leveraging a large variety of data types and cutting-edge modeling techniques. Advanced Analytics is Intel's global internal AI unit and one of the largest Data Science organizations in Israel. We deliver diverse solutions/products that create a 9-digit impact and influence nearly every computer-user in the world.
Advanced Analytics addresses the most critical problems to the company in the domains of product development, manufacturing & sales, and collaborate with Mobileye on their data services.
Advanced Analytics employees are AI experts - Data scientists, Big data engineers, AI Product analysts/managers – working to deliver state-of-the-art solutions & platforms that yields high business impact. We often collaborate with the Academia, provide thought leadership to the industry, and deliver education sessions on AI internally and externally.
Hear about our research Leveraging the Power of Bagging in Multiple Instance Classification| Omer Shalev, IT Advanced Analytics
In contrast to traditional classification approaches in which a model is learned from a set of labeled instances, in Multiple-Instances Classification the model is learned on labeled groups of instances. This presentation shows how Multiple-Instance Classification is applicable in a real use case of bug prediction for hardware validation at Intel Corp. The discussion focuses on existing common approaches which are not suitable for this use case and on the new suggested bagging-based approach which demonstrates promising results on the hardware validation data as well as on a common benchmark dataset.
Watch videoIntel IT Collaboration Leads to Unique Product Innovation – Intel’s Client Computing Group (CCG) defines, designs, and tests new generations of Intel® Core™ processors (as well as other Intel products). CCG engineers recently asked an intriguing question: Might it be possible to use AI and machine learning to dynamically adjust a processor’s power limits, based on the actual workload? Read this article to find the answer.
Read moreDr. Amitai Armon, Intel Advanced Analytics Chief Data Scientist in an interesting conversation with Yochai Schweigger– on TechTime podcast about the people behind the technology.
Hear podcastHear about rising through the ranks in Data Science, a podcast episode with Nufar Gaspar, Data scientist vertical manager in Advanced Analytics. In this episode, Nufar explains how when she was about to graduate with her master's, a friend told her about a group at Intel. Nufar decided to go interview with them because her friend insisted she would be a good fit. At the time, she didn't even realize she wanted to work in the data space. Intel explained how they were working on machine learning and wanted Nufar to join a team of about thirty men. Looking back, it was a perfect match because Nufar is passionate about education and problem-solving. Machine learning is the ideal match for these passions. Now, the team is almost 200 people and rebranded as Advanced Analytics – they work in seven different verticals at Intel. Each vertical is highly focused on transforming the way business is run using AI.
Hear podcastFor sales and marketing organizations within large enterprises, identifying and understanding new markets, customers and partners is a key challenge. Intel’s Sales and Marketing Group (SMG) faces similar challenges while growing in new markets and domains and evolving its existing business. In today’s complex technological and commercial landscape, there is need for intelligent automation supporting a fine-grained understanding of businesses in order to help SMG sift through millions of companies across many geographies and languages and identify relevant directions. Read this study to Learn more about Advanced Analytics system, developed in our company that mines millions of public business web pages, and extracts a faceted customer representation.
Read moreSafety system sensors in modern cars are collecting data about the road on behalf of the company that makes them. Read more about Advanced Analytics and Mobileye joint effort on their data services
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EGI is a fast-paced, dynamic, and startup-like group within Intel responsible for researching, incubating, and developing next-generation technologies and ideas, with a strong orientation towards computer vision, machine learning, data, and AI. The group hosts a diverse team of scientists, engineers, and developers to research, realize, and bring to market innovative new products, leveraging cutting-edge technologies, skills, and capabilities.
Mobileye, an Intel Company, is a global leader in the development of computer vision and machine learning, data analysis, localization, and mapping technologies for Advanced Driver Assistance Systems and autonomous driving solutions. Our safety technology is integrated into hundreds of new car models from the world’s major automakers: BMW, Audi, Volkswagen, Nissan, Ford, Honda, General Motors, and more.
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Until now, you’ve watched sports from the outside looking in. Using cutting-edge cameras, software algorithms, and high-performance computing (HPC), Intel® True View and Intel® True VR add new dimensions to viewing the game, transporting you into the stadium and inside the play.
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A career at Intel will be many different things over time. The opportunity to grow. The chance to learn and develop. And, of course, the opportunity to work on ground-breaking technology that has a very real and positive impact on the world. Here is what we all want from work: inspirational colleagues, a sense that we’re growing in our careers and ourselves, and to know that we’ve made a difference, in some small or large way, to the world that we all share. To be able to answer one simple question with the reply “Amazing things.”
We are looking for candidates with a desire to create new breakthrough technologies. You will have an interest in identifying and exploring compelling new technologies, a sense of entrepreneurship, and the creativity to think of innovative Artificial Intelligence solutions
We have the dream job for Data Scientists:
We have a variety of rich datasets and we are working in diverse and exciting areas of practice. Our data-scientists utilize “classical machine learning”, Deep learning, NLP, computer-vision, reinforcement learning, online learning and more. You will use the state-of-the-art AI methods to solve challenging and unique tasks, which may affect almost every computer-user. You will use a variety of Python AI tools (including Keras, TensorFlow, PyTorch and more), and you will keep learning new things, both as part of your daily job and in our training courses and seminars. The results of your applied research may be presented in leading international AI conferences.
We are looking for successful candidates who can immediately engage on AI SW projects, apply their skills, and quickly begin making progress through the team. You will bring a passion for Artificial Intelligence and an eagerness to be a part of a global Artificial Intelligence
We are looking for candidates that bring a deep experience in hardware and are able to adapt what they know to the unique requirements of Artificial Intelligence. As this is a growing and fast paced field, a sense of urgency and the ability to meet deadlines is important.
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