We value curiosity, innovation, and an ambitious mindset.
Ability to do impactful ML work, learn from other industry-leading minds, contribute to successful outcomes, publish/attend top tier ML conferences, win competitive challenges as a team and get recognized.
Solid track record in academia and industry to untangle the world’s most complex problems. Access to unique datasets and agile team. Short time to production means seeing meaningful impact quickly.
Immerse yourself in our culture of learning where you can grow and learn at the cutting edge of ML.
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At Layer 6 I get to work at the intersection of real-world problems and difficult mathematics. The models we build & deploy within TD ensure that we’re able to handle the challenges of making meaningful predictions from massive & noisy datasets, while our research projects enable us to keep up to date with the latest ML research. The best thing about working here is that everyone brings something to the table — each of my colleagues understands some things that no one else in the office does.
Harry BravinerMachine Learning Scientist
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Layer 6 offers me the great opportunity to participate in cutting-edge research in both recommender systems and natural language processing. I love the motivating work environment and being able to work with my brilliant colleagues. The talent and enthusiasm of team is really great and stimulating for me.
Yichao LuMachine Learning Scientist
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Layer 6 values creative people with their own original ideas, and provides wide opportunities and resources for self-realization in return. Everyone is totally possessed by their work. What drives me personally is the ability to make and observe an immediate quantifiable impact of my work, and the freedom to alternate my time between applied use cases and research projects.
Ilya StanevichMachine Learning Scientist
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At Layer 6 I get to work on ambitious problems with smart people who are passionate about driving change with machine learning. We have the opportunity to touch millions of people in really core aspects of their lives, whether in financial services or beyond, and a culture that supports a tremendous amount of intellectual freedom. I love how short the path is between research innovation and application at Layer 6.
Saba ZuberiMachine Learning Scientist
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Layer 6 has no shortage of state-of-the-art research and socially impactful problems to solve in the fields of CV, NLP, Health, and Banking. These days, I’m building recommender systems for TD’s Digital Mobile App to provide Canadians with more financial confidence. Our culture at Layer 6 is great – I find progress to be always more rewarding when you're surrounded by people who get you.
Anson WongMachine Learning Scientist
We care about our employees.
We offer generous packages of pension plans, health coverage, visa support and vacation. We have healthy and low-sugar snacks in the office.
We’re committed to fill your curiosity.
We provide unique opportunities for our team to learn from the researchers at Vector Institute. We encourage everyone to challenge themselves and acquire knowledge at international competitions and conferences. We organize lunch & learn series to share our findings and learn from each other.
We have a driven, diverse, and amiable culture.
We are self-motivated, entrepreneurial, competitive yet humble and nice to each other. We are open minded and provide everyone with equal opportunities to achieve their professional goals. We work extremely hard but still take time to have fun and exciting activities!
Join us
Data Engineer, Machine Learning
Robust, trustworthy, and efficient data system is crucial for developing and deploying ML models in production. In addition to handling the complexity of massive data sources, ML data system also needs to provide strong support for data science specific tasks.
Data Engineer, Machine Learning
Data Engineering team at Layer 6 focuses on building robust data pipelines, machine learning focused data validation system, and centralized asset (data, features, and models) management system.
We aim to provide industry-leading solutions to our machine learning engineers while operating a machine learning platform at scale.
We are looking for experienced data engineers and problem solvers who have worked with tight deadlines and challenging tasks. The ideal candidate will be passionate about data-centric solutions and machine learning systems. The candidate should be able to design and implement components of data system and lead by example. The candidate should also interact with machine learning scientists, the infrastructure team and data sources team to develop systems that will satisfy the needs of machine learning projects.
As a Data Engineer, you will
- Contribute to the planning and execution of data pipelines for various machine learning projects
- Design, implement, and maintain data pipelines with complex data transformations
- Implement key components of data validation and management system
- Perform profiling and troubleshooting of the existing data-centric solutions
- Automate existing manual steps and optimize the overall data transformation processes
Required Qualifications
- BSc+ in Computer Science, Math, Physics, or similar
- 6+ years of extensive programming experience, at least 3 years in building production data systems
- Strong experience with design and development of distributed data processing systems
- Strong experience with major Big Data technologies and frameworks including but not limited to Hadoop, MapReduce, Spark, Cassandra, Kafka, Elasticsearch
- Experience with Big Data solutions developed in large cloud computing infrastructures such as Azure and AWS
- Practical expertise in performance tuning, bottleneck problems analysis, and troubleshooting
Strong experience with Scala and Java 8
Preferred Qualifications
- C++, Python experience
- Experience in systems/infrastructure projects on Linux
- Machine learning experience with knowledge of tools and frameworks such as tensorflow,
- Pytorch, and MXNet
- Deep Learning model training experience with GPUs
Benefits
- Entrepreneurial and inclusive culture
- Excellent health coverage
- Four weeks paid vacation
- Catered lunches twice a week over machine learning talks
Please submit your CV to careers@layer6.ai.
Machine Learning Scientist
In this role you will research, develop, and apply new techniques in the intersection of deep learning and personalization to further advance our industry leading product. We’re looking for someone with a PhD in Computer Science, Statistics, Operations Research, Mathematics or a related field.
Machine Learning Scientist
Layer 6 is a leading machine learning research company, developing advanced deep learning systems that have the power to uplift large populations while advancing the field of artificial intelligence.
Our research is supported by access to massive datasets, close collaboration with world renowned academic faculty, and a uniquely scalable machine learning platform. Research areas include deep learning, computer vision, time series analysis, natural language processing and recommendation systems etc.
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 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
Please submit your CV to careers@layer6.ai.
Our team is growing fast
We’re always looking for ambitious, execution-oriented people. Submit your CV to careers@layer6.ai and let’s chat.
Our hiring process
Apply
Start by submitting your CV. If your credentials meet the requirements for the role, we’ll schedule an in-person interview at our MaRS offices in downtown Toronto.
Technical test
Your first interview will be conducted with the appropriate tech lead. You will complete three stages (Math, Coding and ML) of technical testing to assess your relevant problem solving abilities.
Final interview
Following the technical interview, you will meet with one of our founders to discuss your previous work/school experience and your aspirations in machine learning.
Receive offer
Only the most technically accomplished candidates with a strong culture fit will be offered employment packages.
Technical test sample questions
Coding Question: Implement a function to compute the number of occurrences of a digit k in all numbers between a and b where a >=0 and b >= a. Estimate the runtime of your function. You can use Java, C++, Python or Scala.
Math Question #1: Write a function sample_x( ) to draw independent samples of a random variable with probability density function
Assume you have a function RNG( ) that returns independent floats uniformly distributed in [0,1]. Can you find a way of doing this that runs in a deterministic amount of time?
Math Question #2: Consider the loss function L(x, y) = ½ ( ax² + by² ). Here x and y are the parameters, and a and b are positive constants. For what values of the learning rate will gradient descent converge to the minimum?