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Added 10 mins ago
Staff Machine Learning Engineer
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Join the team as Twilio’s next Staff Machine Learning Engineer on Twilio’s AI/ML Platform team.
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Research Machine Learning Scientist II (B3617)

Toronto, ON, Canada

$140,000 - $190,000 CADThe pay details posted reflect a temporary market premium specific to this role that is reassessed annually. · Full-time

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Job details

Pay: $140,000 - $190,000 CADThe pay details posted reflect a temporary market premium specific to this role that is reassessed annually.
Job type: Full-time
Apply by: Oct 28, 2026
Experience: 2+ years of research experience with publication record
Posting language: English
Posted: Oct 26, 2026

Original job description

Work Location:

Toronto, Ontario, Canada

Hours:

37.5

Line of Business:

Analytics, Insights, & Artificial Intelligence

Pay Details:

$140,000 - $190,000 CADThe pay details posted reflect a temporary market premium specific to this role that is reassessed annually.

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Job Description:

We are currently in the final stages of the interview process with a preferred candidate. However, we value diverse perspectives and encourage all qualified individuals to apply.

Day-to-day as a Research Machine Learning Scientist:

- 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.

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

Who We Are:

TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches/stores. Every day, we strive to make every interaction, product, and experience remarkably human and refreshingly simple for over 27 million households and businesses in Canada, the United States and around the world. More than 95,000 TD colleagues bring their skills, talent, and creativity to foster deeper relationships, ensure disciplined execution, and build a simpler, faster banking experience. TD is deeply committed to being a leader in client experience, that is why we believe that all colleagues, no matter where they work, are client facing. Together, we are reimagining what banking can be for our clients, colleagues and communities.

Our Total Rewards Package
Our Total Rewards package reflects the investments we make in our colleagues to help them and their families achieve their financial, physical, and mental well-being goals. Total Rewards at TD includes a base salary, variable compensation, and several other key plans such as health and well-being benefits, savings and retirement programs, paid time off, banking benefits and discounts, career development, and reward and recognition programs. Learn more

Additional Information:
We’re delighted that you’re considering building a career with TD. Through regular development conversations, training programs, and a competitive benefits plan, we’re committed to providing the support our colleagues need to thrive both at work and at home.

Please be advised that this job opportunity is subject to provincial regulation for employment purposes. It is imperative to acknowledge that each province or territory within the jurisdiction of Canada may have its own set of regulations, requirements.

Colleague Development

If you’re interested in a specific career path or are looking to build certain skills, we want to help you succeed. You’ll have regular career, development, and performance conversations with your manager, as well as access to an online learning platform and a variety of mentoring programs to help you unlock future opportunities.

If you’re passionate about helping clients and building deep, lasting relationships, TD offers diverse career paths where you can grow your expertise and make a meaningful impact.

We're committed to your success and foster a respectful workplace where diverse perspectives are valued, everyone has fair opportunities to grow, and you can unlock your full potential to achieve your career goals. Here at TD, we hire and develop the best.

Training & Onboarding
We will provide training and onboarding sessions to ensure that you’ve got everything you need to succeed in your new role.

Interview Process
We’ll reach out to candidates of interest to schedule an interview. We do our best to communicate outcomes to all applicants by email or phone call.

Accommodation
Your accessibility is important to us. Please let us know if you’d like accommodations (including accessible meeting rooms, captioning for virtual interviews, etc.) to help us remove barriers so that you can participate throughout the interview process.

We look forward to hearing from you!

Language Requirement (Quebec only):

Sans Objet

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More about this job

Responsibilities

Research, develop, and apply deep learning techniques to advance products using large-scale real-world datasets, including banking transactions and document collections. Collaborate with engineering teams to deploy research in production, continue developing expertise, and present work at leading machine learning conferences.

Requirements

A PhD or master’s degree in computer science, statistics, mathematics, engineering, or a related field is required, along with a strong machine learning and deep learning background. Candidates need at least two years of research experience with publications and a record of applying machine learning to real-world problems; experience with ML frameworks, software systems, data platforms, GPUs, or cloud computing is preferred.

Skills

Machine Learning
Deep Learning
Research
Applied Machine Learning
PyTorch
TensorFlow
JAX
Software Systems Development
Spark
SQL
GPU-Accelerated Training
Cloud Computing
Azure
AWS
Data Analysis

Benefits

Health and Well-Being Benefits
Savings and Retirement Programs
Paid Time Off
Banking Benefits and Discounts
Career Development
Reward and Recognition Programs

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Deep Learning
Artificial Intelligence
Research
Research Publications
Real-World Datasets
Banking Transactions
Document Collections
PyTorch
TensorFlow
JAX
Software Systems Development
Spark
SQL
GPU-Accelerated Training
Cloud Computing
Azure
AWS
Production Deployment
Machine Learning Conferences

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