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TD Securities

Applied Machine Learning Scientist I, Tabular Deep Learning Model Validation

On site

Toronto, Canada

Full Time

06-03-2026

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Skills

Communication Time Management Python Java Scala Research Machine Learning PyTorch TensorFlow Deep Learning Programming Azure Marketing cloud platforms Analytics Artificial Intelligence Natural Language Processing Keras Databricks PySpark Mathematics NLP

Job Specifications

Work Location:

Toronto, Ontario, Canada

Hours

37.5

Line Of Business

Analytics, Insights, & Artificial Intelligence

Pay Details

$105,500 - $125,000 CAD

The 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

Department Overview

TD Model Validation (MV) group is responsible for the independent validation and approval of models used for Generative AI, Natural Language Processing (NLP), Tabular Deep Learning, credit, fraud, and marketing models. The Artificial Intelligence/Machine Learning (AI/ML) MV team is responsible for the validation of all AI/ML models used across the Bank for various use cases.

Job Description

The position reports to Senior Applied Machine Learning Scientist in the AI/ML Model Validation team and is primarily focused on the validation and review of Deep Learning models.

Detailed Accountabilities Include

Research, validate, and apply new techniques in testing deep learning models applied to tabular/structured datasets.
Stay up to date with advancements in the field of AI including major publications, foundation models, evaluation metrics, explainability, technology stacks, and datasets.
In depth knowledge of techniques and developments in the field of AI/ML and share knowledge with business partners and senior management.
Develop/implement AI/ML model validation methodologies and standards, especially for Tabular Deep Learning / Foundation models. Ensure that the validation methodologies and standards are in line with industry best practices and address regulatory and audit requirements.
Work in Distributed Cluster / Cloud environments with large-scale datasets ranging from transactions to large document collections.
Develop and apply a variety of statistical tests and modeling techniques to identify/recommend improvements to models and undertake related initiatives. Implement benchmark models as applicable.
Conduct R&D in the area of Tabular Deep Learning and Foundation Models evaluation, testing, explainability.
Communicate findings and recommendations to both technical and non-technical stakeholders.

The position involves working effectively with different internal partners such as AI2, Layer6, P&T, and FCRM.

Job Requirements
Strong quantitative skills with an advanced degree in one or more of the following areas: computer science, machine learning / AI, engineering, statistics, mathematics, or physics.
Experience with and strong knowledge of AI/ML methodologies including Deep Learning, modern Natural Language Processing (NLP), Transformers, Diffusion models, and Bagging/Boosting methods.
Experience with Deep Learning technology stacks and libraries such as PyTorch, Tensorflow/Keras etc.
Stay up to date with the latest advancements in Tabular Deep Learning / Foundation models, Machine Learning, and Cloud technologies.
Proficient in one or more scripting/programming languages such as Python, Java, Scala, Pyspark.
Familiarity with cloud platforms (e.g., Azure Databricks, Azure ML Studio).
Familiarity with Data Structures, Algorithm design, and principles of Object-Oriented Programming (OOP).
Knowledge of machine learning explain-ability/interpretability algorithms.
Excellent verbal and written communication skills. The position requires writing clean technical reports.
Ability to work independently and collaboratively in a fast-paced, dynamic environment. Great time management and multitasking skills with minimal supervision.
Preferred Qualifications
Publications in the relevant conference and journals are a plus.
Ability to implement AI/ML algorithms from academic research papers is a plus.
Aperçu du service

Le groupe Validation des modèles TD est responsable de la validation et de l’approbation indépendantes des modèles utilisés pour l’intelligence artificielle générative, le traitement du langage naturel, l’apprentissage profond pour les données tabulaires, le crédit, la gestion de la fraude et le marketing. L’équipe Validation des modèles, Intelligence artificielle (IA) et Apprentissage automatique (AA) est responsable de la validation de tous les modèles d’intelligence artificielle et d’apprentissage automatique utilisés à l’échelle de la Banque pour divers cas d’utilisation.

Description du po

About the Company

As a leading corporate and investment bank, TD Securities offers a wide range of integrated capital markets products and services. Our corporate, government, and institutional clients choose us for our innovation, execution, and experience. With 7,000 professionals operating out of more than 30 cities across the globe, we help clients meet their needs today and prepare for tomorrow. Our services include underwriting and distributing new issues, providing trusted advice and industry-leading insight, extending access to global... Know more