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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Working at Layer 6 is an incredible experience because of the brilliant and passionate people I get to collaborate with every day. The team’s dedication and reliability create a motivating and supportive work environment where everyone strives for excellence. It also offers immense freedom to pursue projects and research areas that genuinely interest us, allowing us to make a meaningful impact through our work.
Keyu LongMachine Learning Scientist
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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!
Join us
Software Engineer II – Framework
We are looking for world-class engineers to tackle cutting-edge problems of applying Machine Learning in the real world. Join this team to develop a framework for machine learning models that have real world impact. The goal of the framework is to help our ML Scientists build robust and high performing models through providing a solid foundation and allowing for fast iteration.
Software Engineer II – Framework
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 such as deep learning and generative AI, time series forecasting and 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.
Job Description:
The goal of the ML Engine team is to enable training and deploying robust and high-performing models by providing a solid foundation and allowing for fast iteration. We are looking for world-class engineers to take on the challenging problem of shipping core components of the engine that will be used across the bank. The candidate will be one of the primary engineers for the machine learning engine. They will design critical components of the engine and deliver them from 0 to 1, which will be used across the Bank. The candidate will interact with machine learning scientists, ML Systems teams to develop systems that will satisfy the needs of machine learning projects.
What are your main responsibilities?
- Own and ship product features that enable ML engine capabilities.
- Work with product owners and tech leads to design, ship, and refine significant components of the product.
- Work with scientists and MLOps teams to maintain and service the product.
Required Qualifications:
- 3+ Years of industry experience as a Software Engineer leading the development of features
- Experience with building and scaling data-intensive software.
- You value good software design and sweat over details in code and API design.
- You enjoy learning new technology and educating others.
- You take great personal pride in building robust and scalable software.
- You strive to communicate clearly and with empathy.
- You are highly accountable and have a strong sense of ownership.
- You are a self-starter and can independently drive your projects forward.
- Ability to do detailed code reviews and give thoughtful feedback.
Preferred Qualifications:
- Experience building a library or a framework.
- Experience with Big Data technologies and frameworks including but not limited to Spark, Cassandra, Kafka.
- Experience with Microsoft Azure
- Comfortable with statistics.
- Knowledge of machine learning and deep learning.
- Knowledge of distributed systems.
Please submit your CV to careers@layer6.ai.
Technical Product Owner
You will own the delivery of machine learning solutions & work of up to 5 colleagues. Melding expertise in data science, technology, and product management, you embrace the challenge of solving strategic business problems with innovative, scalable products. You are a natural collaborator and influencer. You resolve complex technical problems and effectively communicate to your audience, both technical & not, to achieve a common vision. You have a passion for building a better solution, every time. You naturally 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 research broadly spans the field of machine learning with areas such as deep learning and generative AI, time series forecasting and 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 Technical Product Owner:
- Translate broad business problems into sharp data science use cases, and craft use cases into product visions
- Own machine learning products from vision to backlog; prioritizing features and defining minimum viable releases; maximizing the value your products generate, and the ROI of your pod
- Guide Agile pods on continuous improvement, ensuring that the next sprint is delivered better than the previous
- Work closely with stakeholders to identify, refine and (occasionally) reject opportunities to build machine learning products; collaborate with support functions such as risk, technology, model risk management and incorporate interfacing features
- Facilitate the professional & technical development of your colleagues through mentorship and feedback
- Anticipate resource needs as solutions move through the model lifecycle, scaling pods up and down as models are built, perform, degrade, and need to be rebuilt
- Championing model development standards, industry best-practices and rigorous testing protocols to ensure model excellence
- Self-direct, with the ability to identify meaningful work in down times and effectively prioritize in busy times
- Drive value through product, feature & release prioritization, maximizing ROI & modelling velocity
- Be an exceptional collaborator in a high-interaction environment
Job Requirements:
- Minimum three years of experience delivering major data science projects in large, complex organizations
- Strong communication, business acumen and stakeholder management competencies
- Strong technical skills: machine learning, data engineering, MLOps, cloud solution architecture, software development practices
- Strong coding proficiency: python, R, SQL and / or Scala, cloud architecture
- Certified Scrum Product Owner and / or Certified Scrum Master or equivalent experience
- Familiarity with cloud solution architecture, Azure a plus
- Master’s degree in data science, artificial intelligence, computer science or equivalent experience
Please submit your CV to careers@layer6.ai.
Senior Technical Product Owner
Melding expertise in data science, technology, and product management, you embrace the challenge of solving strategic business problems with innovative, scalable products. You are a natural collaborator and influencer. You resolve complex technical problems and effectively communicate to your audience, both technical & not, to achieve a common vision. You have a passion for building a better solution, every time. You naturally provide your colleagues with the inspiration and tools to execute with speed and impact, becoming true leaders themselves.
Senior 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 research broadly spans the field of machine learning with areas such as deep learning and generative AI, time series forecasting and 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 Senior Technical Product Owner:
You will own the strategy and roadmap for our ML Engine. You will work closely with the tech lead, Layer 6 and AI/ML team leads, and our engineering teams.
- Engage analytics leads from different businesses, build relationship and gather priorities
- Effectively manage multiple machine learning (ML) workstream priorities, exercising judgement
- Communicate and opine with a product mindset, bring in experts as needed
- Coordination of a diverse set of stakeholders to put together product strategy
- Work with tech and product leads to develop and maintain the ML Engine roadmap, target state, and tradeoffs
- Owns the ML engine product adoption from vision to backlog; identify new opportunity and prioritize features to define minimum viable releases; maximizing the value and the ROI of the ML Engine team
- Be an exceptional collaborator in a high-interaction environment
Job Requirements
What can you bring to TD? Tell us about your most relevant experience, credentials and knowledge for this role, as well as these essential requirements and attributes:
- Minimum three years of experience delivering major data science projects in large, complex organizations
- Strong communication, business acumen and stakeholder management competencies
- Strong technical skills: machine learning, data engineering, MLOps, cloud solution architecture, software development practices
- Strong coding proficiency: python, R, SQL and / or Scala, cloud architecture a plus
- A track record of driving product adoption and growth
- Familiarity with cloud solution architecture, Azure a plus
- Certified Scrum Product Owner and / or Certified Scrum Master or equivalent experience a plus
- Master’s degree data science, artificial intelligence, computer science or equivalent experience
Please submit your CV to careers@layer6.ai.
Machine Learning Engineer
We are looking for experienced Machine Learning Engineers who have worked under tight deadlines and on challenging tasks. The ideal candidate is a strong coder with solid machine learning engineering experience. They should also have expertise in data engineering, machine learning system design and MLOps.
Machine Learning Engineer
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 such as deep learning and generative AI, time series forecasting and 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.
Key Responsibilities:
- Traditional ML: Develop and deploy batch and real-time model inference pipelines to production, perform end-to-end integration testing.
- Gen AI: Develop and deploy scalable production Gen AI systems for Gen AI models.
- Mode Serving Framework: Develop in house model serving framework or integrate open-source model serving framework with enterprise data platform.
- ML System Design: Architect scalable machine learning and Gen AI systems that integrate with existing data platform and infrastructure, focusing on automation, operation efficiency, and reliability.
- Data Analysis & Processing: Perform data analysis, data preprocessing, and feature engineering on complex and large datasets for machine learning models.
- Model Deployment & Monitoring: Build and deploy model inference pipeline, ground truth pipeline, model monitoring pipeline to production environment. Continuously monitor production model performance and system performance
- Automation: Build CI/CD pipelines to automate model deployment, model deployment validation, model performance monitoring, and model retraining.
- Research: Stay up to date with the latest advancements in AI/ML technologies and apply them to improve existing ML systems or develop new systems and solutions.
- Technical Leadership: 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.
- Collaboration: 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.
Job Requirements:
Required Technical Qualifications:
- BSc+ in Computer Science, Math, Physics, or similar
- 2+ years of extensive programming experience, 1+ year experience of building machine learning production system
- Solid knowledge of applied Machine Learning, Deep Learning, Large Language Models
- Experience with developing MLOps CI/CD pipelines for deploying AI/ML models
- Solid cloud experience with Azure or AWS and cloud AI/ML services such as Databricks, Kubernetes, docker and container orchestration, Azure Machine Learning, Azure Data Factory
- Strong experience with PySpark for big data processing and PyTorch for deep learning model serving
- Expert coder with Python, Java, or Scala
- Experience with RAG, LLM fine tuning, LLM serving
- Practical expertise in performance tuning, bottleneck problems analysis, and troubleshooting
Preferred Qualifications:
- Knowledge of cloud engineering
- Self-motivated and demonstrated ability to take independent action to delivery results.
- Highly developed critical thinking, analytical and problem-solving skills
- Strong verbal and written communication skills, with the ability to work effectively across teams
Please submit your CV to careers@layer6.ai.
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 that range from banking transactions, to large document collections.
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 such as deep learning and generative AI, time series forecasting and 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.
As a Research Machine Learning Scientist, you will
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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.
Required Qualifications:
- PhD or Master’s degree in Computer Science, Statistics, Mathematics, Engineering or a related field
- Strong background in machine learning and deep learning
- 2+ years of research experience with publication record
- Proven track record of applying machine learning to solve real-world problems
Preferred Qualifications:
- Depth of experience in relevant ML research disciplines
- Hands on experience in software systems development
- Experience with one or more of Pytorch, Tensorflow, Jax, or comparable library
- Experience with Spark, SQL, or comparable database systems
- Experience using GPUs for accelerated deep learning training
- Familiarity with cloud computing systems like Azure or 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 a remote 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?