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 aim high and do good!
We focus on doing a few things really, really well and continue raising the bar year after year. We build solutions with broad, positive impact that we can be proud of.
We’re committed to fill your curiosity.
We share a hunger to learn! Everyone is encouraged to try something ambitious and meaningful, and learn from mistakes and successes in equal measure.
We are inclusive and we win together.
We foster a place where everyone feels included, cared for and safe to be who they are. We help each other succeed and win as a team, as Layer 6!
Join us
Machine Learning Product Engineer
The Machine Learning Product Engineer team at Layer 6 focuses on building industry-leading data-centric systems and model delivery systems. Our solutions include data pipelines, feature data lake, systemic data validation and automation of key activities in model delivery including model validation, shakedown, inference, and maintenance.
Machine Learning Product Engineer
The Machine Learning Product Engineer team at Layer 6 focuses on building industry-leading data-centric systems and model delivery systems. Our solutions include data pipelines, feature data lake, systemic data validation and automation of key activities in model delivery including model validation, shakedown, inference, and maintenance.
We are looking for experienced Machine Learning Product Engineers (MLPE) who have worked under tight deadlines and on challenging tasks. The ideal candidate is a strong coder with solid data engineering experience. They should also have expertise in machine learning, system design and devops.
The candidate will design and implement components of data and model delivery system and lead by example. The candidate will interact with machine learning scientists, the infrastructure team and data sources team to develop systems that will satisfy the needs of machine learning projects.
What are your main responsibilities?
- Implement complex data-centric solutions, including extremely complex and large data set verification, transformation and feature generation, to ensure continuous high-quality input for the model development
- Build model delivery systems, including inference pipeline, automatic model validation reports generation, automatic model performance monitoring and model retraining, to ensure fast model productionization and reliable production system
- Maintain the model in production and ensure the data/model related knowledge continuation within L6
Required Technical Skills
- BSc+ in Computer Science, Math, Physics, or similar
- 2+ years of extensive programming experience, at least 1 year in building production data systems
- 1+ year experience of building machine learning production system
- Strong experience with major Big Data technologies and frameworks including but not limited to Hadoop, MapReduce, Spark, Cassandra, Kafka, Elasticsearch
- Good knowledge of Machine Learning and Deep Learning
- Practical expertise in performance tuning, bottleneck problems analysis, and troubleshooting
- Strong experience with Scala and Java 8
Nice to have Skills
- C++, Python experience
- Experience in systems/infrastructure projects on AWS and Azure
Benefits
- Entrepreneurial and inclusive culture
- Excellent health coverage and pension plan
- Four weeks paid vacation
- Catered lunches twice a week over machine learning talks
Please submit your CV to careers@layer6.ai.
Sr. Machine Learning Product Engineer
The Machine Learning Product Engineer team at Layer 6 focuses on building industry-leading data-centric systems and model delivery systems. Our solutions include data pipelines, feature data lake, systemic data validation and automation of key activities in model delivery including model validation, shakedown, inference, and maintenance.
Sr. Machine Learning Product Engineer
The Machine Learning Product Engineer team at Layer 6 focuses on building industry-leading data-centric systems and model delivery systems. Our solutions include data pipelines, feature data lake, systemic data validation and automation of key activities in model delivery including model validation, shakedown, inference, and maintenance.
We are looking for experienced Senior Machine Learning Product Engineers (Sr. MLPE) who have worked under tight deadlines and on challenging tasks. The ideal candidate is a master of coding and system design. They also are experts in data engineering and/or machine learning.
The candidate will be the go-to person for data and model delivery. They will lead and coordinate efforts of members on the MLPE team to ensure best engineering practice in our systems. The candidate will interact with machine learning scientists, the infrastructure team and data sources team to develop systems that will satisfy the needs of machine learning projects.
What are your main responsibilities?
- Lead the design and implementation of complex data-centric solutions, including extremely complex and large data set verification, transformation and feature generation, to ensure continuous high-quality input for the model development
- Lead the design and implementation of model delivery systems, including inference pipeline, automatic model validation reports generation, automatic model performance monitoring and model retraining, to ensure fast model productionization and reliable production system
- Go-to person for data and model delivery within Layer 6
- Lead and mentor Machine Learning Product Engineers to ensure best engineering practice in our systems.
Required Technical Skills
- BSc+ in Computer Science, Math, Physics, or similar
- 5+ years of extensive programming experience, at least 3 years in building production data systems
- 3+ years experience of building machine learning production system
- Expert level skills in system design
- Expert in Big Data technologies and frameworks including but not limited to Hadoop, MapReduce, Spark, Cassandra, Kafka, Elasticsearch
- Strong knowledge of Machine Learning and Deep Learning
- Practical expertise in performance tuning, bottleneck problems analysis, and troubleshooting
- Experience with Big Data solutions developed in large cloud computing infrastructures such as Azure and AWS
- Strong experience with Scala and Java 8
Nice to have Skills
- C++, Python experience
Benefits
- Entrepreneurial and inclusive culture
- Excellent health coverage and pension plan
- Four weeks paid vacation
- Catered lunches twice a week over machine learning talks
Please submit your CV to careers@layer6.ai.
Sr. DevOps Engineer
You will join the team in solving the challenges of developing high performance, robust and scalable machine learning solutions and delivering them in production.
Sr. DevOps Engineer
You will join the team in solving the challenges of developing high performance, robust and scalable machine learning solutions and delivering them in production.
We are looking for world-class devops engineers and problem solvers. You will be interacting with machine learning scientists and engineers to develop and automate machine learning pipelines that work. In particular, you will participate in the development, delivery and automation of scalable systems for data ingestion, processing, validation, model training, large-scale computation, monitoring, serving results and handling upgrades.
Required Skills
- 5+ years of experience building sophisticated and automated infrastructure
- Prior success in automating a real-world production environment
- Experience with seamless/automated build scripts used for release management across all environments
- Experience with managing CI/CD tools and pipelines
- Experience with docker and container orchestration
- Understanding and experience with deploying microservices
- Solid Azure and AWS experience
- Strong scripting skills, i.e., Bash, Python etc.
- Knowledge of IP networking, VPN’s, DNS, load balancing and firewalls
- Strong practical Linux systems administration skills in a Cloud environment, Redhat and Ubuntu
- Strong verbal and written communication skills, with the ability to work effectively across teams
- Experience with Git, Jenkins, Elasticsearch
- Experience with automated testing tools
- Familiarity with monitoring tools
- Experience with troubleshooting and tuning systems performance
- Knowledge of Java, C++ build tools
- BA/BS degree or equivalent experience; Computer Science or Math background preferred
Nice to have Skills
- Java, Scala, C++, Python experience
- Big Data experience
- GPU experience
Benefits
- Entrepreneurial and inclusive culture
- Excellent health coverage and pension plan
- Four weeks paid vacation
- Catered lunches twice a week over machine learning talks
Please submit your CV to careers@layer6.ai.
Sr. Full Stack Engineer
We are looking for world-class engineers to help us develop a system that will serve as the main interface to our machine learning platform. The goal of this system is to help in all stages of model development, from feature engineering all the way to production monitoring.
Sr. Full Stack Engineer
We are looking for world-class engineers to help us develop a system that will serve as the main interface to our machine learning platform. The goal of this system is to help in all stages of model development, from feature engineering all the way to production monitoring.
We empower our data scientists to build better models by helping them understand the data and trained models. We also provide the tools necessary for analyzing and visualizing machine learning algorithms in an effort to extract valuable business insights in a transparent and comprehensive manner.
As Senior Full Stack Engineer at Layer 6, you’ll work with data scientists to learn about different machine learning algorithms and ways to analyze them. On the back end, you’ll work with the team to architect systems and design a REST API for the front-end web application, while on the front-end, you’ll build intuitive interfaces to visualize data and answer questions about machine learning models.
You’ll also have the opportunity to work with the engineering team to tackle the challenge of developing high performance, robust and scalable systems.
Requirements
What can you bring to TD & Layer 6? Share your credentials, but your relevant experience and knowledge can be just as likely to get our attention. It helps if you have:
- BSc+ in Computer Science or similar
- 5+ years of programming experience
- Proven experience in designing and delivering a large web application
- Experience as a key contributor and leader on projects
- Strong experience in Java or JavaScript (or other front-end languages)
- Extensive experience with at least one front-end framework (React, Elm, etc.)
- Passionate about creating a great user experience
- Strong desire to learn
What we consider an asset:
- Experience in building a web app in Elm
- Experience with functional programming
- Experience with Elasticsearch
- Familiarity with data analysis or machine learning
- Experience with Docker and Kubernetes
- Comfortable with math (linear algebra, calculus)
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.
Sr. Backend Engineer
We are looking for world-class engineers to help us develop a system that will serve as the main interface to our machine learning platform. The goal of this system is to help in all stages of model development, from feature engineering all the way to production monitoring.
Sr. Backend Engineer
We empower our machine learning scientists to build better models by helping them understand the data and trained models. We also provide the tools necessary for analyzing and visualizing machine learning algorithms in an effort to extract valuable business insights in a transparent and comprehensive manner.
As Senior Backend Engineer at Layer 6, you’ll work with ML scientists to learn about different machine learning algorithms and ways to analyze them. On the back end, you’ll work with the team to architect systems and design a API for the front-end web application which will visualize data and answer questions about machine learning models.
You’ll also have the opportunity to work with the engineering team to tackle the challenge of developing high performance, robust and scalable systems.
Requirements
- BSc+ in Computer Science or similar
- 5+ years of programming experience
- Proven experience in designing and delivering a complex web application
- Experience as a key contributor and leader on projects
- Strong experience in Java and its ecosystem
- Passionate about creating maintainable and performant software
- Strong desire to learn and solve problems
What we consider an asset:
- Experience with databases such as Elasticsearch
- Experience with microservice architecture
- Familiarity with data analysis or machine learning
- Experience with Docker and Kubernetes
- Comfortable with math (linear algebra, calculus)
Benefits
- Entrepreneurial and inclusive culture
- Excellent health coverage and pension plan
- 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?