We value curiosity, innovation, and an ambitious mindset.
We are looking for people who are inspired to do impactful ML work, learn from other industry-leading minds, publish at and attend top tier AI conferences, solve challenges as a team and be recognized for success.
Our ideal candidates have a solid track record in industry or academia. We value foundational contributions to research and open source projects, experience with deploying complex ML systems, and exceptional collaboration.
Immerse yourself in our culture of learning where you can grow and learn at the cutting edge of ML.
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In my life at Layer 6, I get to use cutting-edge technologies to build and deploy models for TD with industry-leading model delivery systems on cloud. As a Machine Learning Systems Engineer, I thrive on seeing impact. Thus, releasing frameworks, pipelines and models to production environments and putting them on a “GO-LIVE” mode is my favourite part of my role. Cause that’s when the product can actually get utilized and bring business value. I love my team and working with my team. All my team members are really good. We learn from each other and we are not afraid to ask for help while pushing each other to raise the bar.
Farnush FarhadiMachine Learning Engineer
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I like working at Layer 6 because the work is never repetitive. Our focus is on innovating and pushing the boundaries of what is possible. There’s a clear link between our research and real-world applications, allowing us to see the tangible impact of our efforts. We blaze the trail for new modelling techniques, and once successful, we build the tools and patterns to scale our impact. Layer 6 is full of strategic, creative, and persistent people who come together to make our projects a success.
Michelle LevineLead Product Owner
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 ignite 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!
Explore roles at Layer 6
Technical Product Owner
Own the delivery of ML solutions by spearheading a team of scientists and engineers. Meld your expertise in data science, technology, and product management to solve strategic business problems with innovative, scalable products. Collaborate and effectively communicate to your audience, both technical and not, to achieve a common vision. Show your passion for building a better solution, every time. Provide your colleagues with the inspiration and tools to execute with speed and impact, becoming true leaders themselves.
Technical Product Owner
Layer 6 is the AI research centre of excellence for TD Bank Group. We develop and deploy industry-leading machine learning systems that impact the lives of over 27 million customers, helping more people achieve their financial goals and needs.
Our products impact the Bank at the highest level by solving the most technically challenging problems with advanced AI. We specialize in the holistic design and development of solutions that directly resolve business needs using cutting edge technologies like generative AI and foundation models.
We are always looking for people driven to be at the cutting edge of machine learning in research, engineering, and impactful applications.
Day-to-day as a Technical Product Owner:
- Translate broad business problems into sharp data science use cases, and craft them into product visions
- Own machine learning products from ideation to implementation, prioritizing features and defining minimum viable releases to maximize the value your products generate
- Guide Agile pods on continuous improvement, ensuring that the next sprint is delivered better than the previous
- Work closely with stakeholders to identify and refine opportunities
- Collaborate with support functions such as risk, technology, and compliance to ensure proper governance
- Facilitate the professional and technical development of your colleagues through mentorship and feedback
- Anticipate resource needs to scale pods up or down as products move through the model lifecycle
- Champion model development standards, industry best-practices, and rigorous testing protocols to ensure model excellence
- Self-direct your work by effectively prioritizing time and identifying meaningful opportunities for growth
- Drive value through product, feature, and release prioritization to maximize ROI and modelling velocity
- Be an exceptional collaborator in a high-interaction environment
We are excited to chat with you!
Machine Learning Engineer
Tackle cutting-edge problems in ML applied to the real world. Build standardized frameworks to launch AI models that have real-world impact. Work with large scale, real-world datasets spanning multiple modalities, ranging from banking transactions, to conversation transcripts and large document collections.
Machine Learning Engineer
Layer 6 is the AI Centre of Excellence for TD Bank Group. We develop and deploy industry-leading machine learning systems that impact the lives of over 27 million customers, helping more people achieve their financial goals and needs.
Our engineering stack supports the development and deployment of ML models across the enterprise including predictive and generative AI. As one of the largest banks in North America, we scale ML deployments to act on massive financial datasets.
We are always looking for people driven to be at the cutting edge of machine learning in research, engineering, and impactful applications.
Day-to-day as a ML Engineer:
- Develop and deploy batch and real-time predictive model inference pipelines, performing end-to-end integration testing
- Develop and deploy production generative AI systems, using cutting-edge frameworks and models
- Engineer in-house model serving frameworks and integrate open-source tooling with an enterprise data platform
- Architect scalable predictive and generative AI systems focusing on automation, operation efficiency, and reliability
- Perform data analysis, preprocessing, and feature engineering on complex and large datasets for ML pipelines
- Build and deploy inference and model monitoring pipelines for production environments to continuously monitor system performance
- Build CI/CD pipelines to automate model deployment, validation, monitoring, and retraining
- Stay up to date with the latest advancements in AI/ML technologies and apply them to improve existing systems or develop new solutions
- Provide technical expertise with a focus on efficiency, reliability, scalability, and security; includes planning, evaluating, recommending, designing, operationalizing, and supporting solutions in compliance with enterprise and industry standards
- Work with machine learning scientists, product owners, data platform team, and business partners to gather use case requirements and implement technical solutions for production AI/ML models
We are excited to chat with you!
Research Machine Learning Scientist
Research, develop, and apply new techniques in deep learning to advance our industry leading products. Work with large-scale, real-world datasets across modalities of tabular, text, image, and more. Share your work globally with publications in top ML venues.
Research Machine Learning Scientist
Layer 6 is the AI research centre of excellence for TD Bank Group. We develop and deploy industry-leading machine learning systems that impact the lives of over 27 million customers, helping more people achieve their financial goals and needs.
Our research broadly spans the field of machine learning with areas including deep learning, generative AI, time series forecasting, and the responsible use of AI. We have access to massive financial datasets and actively collaborate with world renowned academic faculty.
We are always looking for people driven to be at the cutting edge of machine learning in research, engineering, and impactful applications.
Day-to-day as a Research Machine Learning Scientist:
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- 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 deep learning to advance our industry leading products.
- Work with large-scale, real-world datasets that range from banking transactions, to large document collections.
- Collaborate closely with our engineering team in a fast-paced startup environment and see your research deployed in production with very short turnaround.
- Grow your expertise by continuously learning new skills and exploring advanced topics in AI with a team that thrives on knowledge-sharing.
- Represent the team at leading ML conferences, present your research, and stay at the forefront of the field.
We are excited to chat with you!
Our team is growing fast
We’re always looking for ambitious, execution-oriented people. View our current openings here
Any questions? Reach out to layer6@td.com and let’s chat.
Our hiring process
Apply
Start by submitting your application via our job posting. If your credentials meet the requirements for the role, we’ll schedule a virtual or in-person interview at our MaRS offices in downtown Toronto.
Technical tests
Your main interviews will be conducted with the appropriate team lead. Based on your desired role you will complete a combination of technical tests in ML, coding, engineering design and mathematics/statistics to assess your relevant problem solving abilities.
Final interview
Following the technical interviews, you will meet with one of our senior leads to discuss your previous work/school experience and your aspirations in machine learning.
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?