Our technical capabilities have been publicly recognized through a number of wins in various international machine learning competitions, including the prestigious ACM Rec Sys 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 fast 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
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