Our technical capabilities have been publicly recognized through a number of wins in various international machine learning competitions, including the prestigious ACM RecSys Challenge (the only repeat winner in 2017 and 2018 and runner-up in 2019), Google’s Landmark Retrieval Challenge (2nd place in 2018, 3rd place in 2019), Kaggle: RSNA Pneumonia Detection Challenge (4th place in 2018) and the Stanford Question Answering Dataset (2nd place in 2019).
Layer 6 was founded in Toronto in 2016 and backed by some of the most successful technology entrepreneurs in Canada. Layer 6 was acquired by TD Bank Group in 2018 and we continue being based in Toronto’s Discovery District – MaRS Centre.
As a machine learning scientist, you will
Join a world-class team of machine learning researchers with an extensive track record in both academia and industry.
Research, develop, and apply new techniques in the intersection of deep learning and personalization to further advance our industry leading product.
Work with diverse real-life datasets that range from banking transactions, to predictive health applications, to audio/video consumption.
Collaborate closely with the engineering team in a quick paced startup environment and see your research deployed in production with very short turnaround.
Required Qualifications
PhD degree in Computer Science, Statistics, Operations Research, Mathematics or related field
Strong background in machine learning
5+ years of research experience with publication record
Proven track record of applying machine learning to solve real-world problems
Preferred Qualifications
Experience with deep learning and/or collaborative filtering
Hands on experience in software systems development and SaaS applications
Experience with one or more Java, Matlab, Scala, Tensorflow and MXNet
Experience using GPUs for accelerated deep learning training
Familiarity with AWS
Benefits
Entrepreneurial and inclusive culture
Excellent health coverage
Four weeks paid vacation
Catered lunches twice a week over machine learning talks
Opportunities to collaborate with faculty at the Vector Institute