Job Specifications
Lieu De Travail
Toronto, Ontario, Canada
Horaire
37.5
Secteur D’activité
Analyses, informations et intelligence artificielle
Détails De La Rémunération
$105,500 - $125,000 CAD
Les renseignements sur la rémunération publiés tiennent compte d’une prime de marché temporaire propre à ce poste, qui est réévaluée chaque année.
La TD a à cœur d’offrir une rémunération juste et équitable à tous les collègues. Les occasions de croissance et le perfectionnement des compétences sont des caractéristiques essentielles de l’expérience collègue à la TD. Nos politiques et pratiques en matière de rémunération ont été conçues pour permettre aux collègues de progresser dans l’échelle salariale au fil du temps, à mesure qu’ils s’améliorent dans leurs fonctions. Le salaire de base offert peut varier en fonction des compétences et de l’expérience du candidat, de ses connaissances professionnelles, de son emplacement géographique et d’autres besoins particuliers du secteur et de l’entreprise.
En tant que candidat, nous vous encourageons à poser des questions sur la rémunération et à avoir une conversation franche avec votre recruteur, qui pourra vous fournir des détails plus précis sur ce poste.
Description Du Poste
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 Appr