Tag Archives: deep learning

14 AI Companies Hiring Now in Toronto

Update: We have recently learned that both Amazon and Uber are hiring for AI tech jobs in Toronto such as AI Research Scientist (Self Driving), Computer Vision & Machine Learning Engineer/Research, and Data Scientist.

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Artificial intelligence took off like a wild fire in the last few years with Federal Government of Canada supporting the industry with millions of dollars in grants.

Not surprising Toronto has taken a lead in this AI domain, and has over 45 active artificial intelligence organizations employing over 1,500 employees and raised more than $170 million dollars.

Below we list the most prominent 14 leaders in AI space in the Greater Toronto Area as well as Waterloo.

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Top Artificial Intelligence AI Companies Hiring in Toronto



Aislelabs’ technology transforms brick and mortar locations to smart venues, resulting in effective marketing, increased sales, and better customer satisfaction. We serve enterprise customers globally including major shopping centres, airports, transit hubs, big box retail chains and venues.

Angoss Software 


Angoss is a global leader in delivering predictive analytics to businesses looking to improve performance across risk, marketing and sales. With a suite of big data analytics software solutions and consulting services, Angoss delivers powerful approaches that provide you with a competitive advantage by turning your information into actionable business decisions.



For biomedical researchers who are starting experiments, BenchSci is a reagent intelligence platform that transforms published data into experiment-specific recommendations to reduce time, money and uncertainty in planning materials and methods.

Canopy Labs


Every customer reaches a buying decision in their unique way – Canopy Labs helps businesses to track and optimize their customer journey.


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Our goal for the Hubba Discovery Network is to be the first place buyers and influencers start every journey to learn about interesting and new brands and products. We are product people, too, and we built a site for product people like you.


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PumpUp is a positive community to share and achieve your health goals. The PumpUp community is a safe and supportive space to share your journey toward a healthy body and healthy mind. Share your challenges and triumphs, track your fitness, and receive unparalleled support from a global community of like-minded people. PumpUp equips you with the tools you need to live a healthy lifestyle in a positive way. With millions of inspiring people cheering you on, it’s never been easier to become the best version of you!


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We believe that making intelligent decisions can be made easier with AI and today we have multi-billion-dollar clients with retail brands operating in North America, Europe, and Asia.


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StackAdapt is the no. 1 performing native advertising platform helping brands accelerate customer engagement and acquisition. This state-of-the-art platform is where some of the most progressive work in machine learning meets cutting-edge user experience. Ranking the highest in customer satisfaction and performance by G2 Crowd in the DSP category for the fourth time, StackAdapt is one of the fastest growing companies in Canada and ranks 6th in Deloitte’s Technology Fast 50 ranking and 23rd in Fast 500 in North America.

Kognitive Marketing


At Kognitive Marketing we create engaging experiential marketing campaigns that consumers actually want to participate in, thus increasing customer conversions and maximizing sales and brand equity for the client.


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Maropost is a B2C cloud-based revenue optimization suite that gives companies the ability to increase multi-channel customer engagement to maximize revenue. Through integrated marketing and sales automation, Maropost provides essential tools, strategic guidance, and support needed to create more personalized customer experiences through a 360-degree business view – from marketing automation to CRM, commerce, and customer support.


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Naborly has reinvented how credit reports and scores work for the rental industry to help landlords know who they’re renting to, while helping tenants build credit by just paying their rent!



Together with its global team of creative problem-solvers, Nanoleaf is ushering in a new era of beautifully personalized lighting experiences. This brave new world extends far beyond the lightbulb and into a new reality where lighting transforms to meet your needs for every moment of every day. Every product created by Nanoleaf embodies our philosophy of ‘Smarter by Design.’



Viafoura empowers over 600 media brands to engage, discover, and grow their audience through seamlessly integrated user registration, engagement, moderation, and analytics modules–all in one platform.



Zoom.ai is SaaS start-up, utilizing artificial intelligence (AI) to enrich all employees’ work experience while increasing workplace productivity. Zoom.ai operates like a virtual helper, chatting with each employee in their favorite chat application and off-loading repetitive, low-value, day-to-day tasks. Key tasks include document generation, corporate information discovery, and full lifecycle calendaring.

Montreal / Waterloo Maluuba, AI deep learning startup, has been acquired by Microsoft

Microsoft has agreed to acquire Maluuba, a Montreal Waterloo based company with one of the world’s most impressive deep learning research labs for natural language understanding. Maluuba’s expertise in deep learning and reinforcement learning for question-answering and decision-making systems will help Microsoft advance their strategy to democratize AI and to make it accessible and valuable to everyone — consumers, businesses and developers.

No purchasing costs were disclosed.

Two Maluuba co-founders could not be happier – they wrote:

“Back in 2010, as classmates in our AI class (CS 486) at the University of Waterloo, we started to think about the way humans interacted with machines. Graphical User Interfaces (GUI) had been in use for 30 years and yet, they hadn’t changed much. For simple tasks they were easier to use than the command line interfaces, but for complex tasks we still resorted back to programming. We wondered why was this the case? Why couldn’t we just interact with computers the same way we interacted with each other everyday? We had to go to first principles and came to the realization that in order to achieve this level of natural interaction, we had to first develop algorithms that understand the way human beings communicate. Therefore, we had to have a very deep understanding about the fundamentals of human language; our memory and reasoning capabilities; as well the decision making process in our brain.

A couple of years later, we started to develop technology that could solve some of the basic problems of language understanding. At the time, the language understanding community (both academia and industry) was very intrigued by the early success of statistical machine learning algorithms in Personal Assistant systems like Siri. Users could make voice commands and do simple tasks like finding the weather, making a restaurant reservation or even playing some music from the phone. Besides the fact that these systems were extremely unscalable (built by engineers in a domain-by-domain fashion), brittle (keyword style queries worked) and gave users a very poor experience, these systems had a more fundamental flaw – they lacked the intelligence that humans have. In fact, this fallacy didn’t just hold for Personal Assistants, this was true for every machine out there. Machines just don’t think, reason or learn from their mistakes like we humans do. Machines neither have any common sense reasoning, nor they do have short-term, long-term or working memory like us.

In early 2014, we observed that great leaps had been achieved in the fields of computer vision and speech recognition through the application of Deep Learning algorithms. We were excited – if deep learning techniques could enable machines to see and hear like humans, then why not communicate like humans? As we all know, understanding human language is extremely complex and is ultimately the holy grail in the field of Artificial Intelligence. We finally saw a great opportunity to apply Deep Learning and Reinforcement Learning techniques to solve fundamental problems in language understanding, with the vision of creating a truly literate machine – one that could actually read, comprehend, synthesize, infer and make logical decisions like humans. This meant we had to heavily invest in research, therefore we started our Research lab in Montréal in late 2015 (in addition to our awesome engineering team in Waterloo). Our research lab, located at the epicentre of Deep Learning, is focused on advancing the state-of-the-art in deep learning for human language understanding. We have built a team of top Deep Learning Research Scientists and Engineers from around the world and built partnerships with leading academics in the field. We are extremely proud of the breakthroughs we have accomplished over the course of the year. So where are we in our quest for achieving ‘Machine Literacy’? Well, we are just getting started and are excited about the long road ahead.”

Harry Shum, EVP of Microsoft’s AI and research group, said :

“Maluuba’s impressive team is addressing some of the fundamental problems in language understanding by modeling some of the innate capabilities of the human brain, from memory and common sense reasoning to curiosity and decision making,” said Shum. “I’ve been in the AI research and development field for more than 20 years now, and I’m incredibly excited about the scenarios that this acquisition could make possible in conversational AI.”