Work Location:
Montréal, Quebec, Canada

Hours:
37.5

Line of Business:
Analytics, Insights, & Artificial Intelligence

Pay Details:
$156,500 - $190,000 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

The Model Validation (MV) group is a centralized Model Risk Management function within the Bank. It has seen fast growth in the past few years reflecting global regulators' increasing attention on model risk. The Artificial Intelligence / Machine Learning (AI/ML) Model Validation (MV) group is responsible for the review/vetting and approval of AI/ML models developed and used across the enterprise (e.g., Fraud, Retail Credit Risk, Marketing, NLP, TD Wealth, TD Asset Management, Treasury Balance Sheet Management, TD Insurance, TD Securities), including Generative AI and other contemporary Deep Learning models.

* Job Description

The position reports to the AVP, AI/ML Model Validation group and is primarily focused on leading the team responsible for the review/vetting of Generative AI, NLP and other Deep Learning models.

Detailed accountabilities include:

• Lead R&D in the GenAI/Agentic/LLM evaluation and testing areas.
• Lead a team of Machine Learning Scientists to perform validation of complex AI/ML models, particularly Generative AI, LLMs / NLP and Deep Learning models.
• Validate (review, test/evaluate, and provide effective challenge to the model developers) AI/ML models, particularly Generative AI and Deep Learning models.
• Recommend the approval of models or other corrective actions based on the independent validation.
  • Lead and support a team of model validators.
  • Ensure performance objectives are set for all staff and that performance feedback is provided on a regular basis.
  • Communicate group objectives and strategies and align group activities in support of business objectives.
• Support employee development activities, coach and support direct reports in meeting their personal development objectives.
• Assume a leadership role in developing standards and procedures for vetting and validation of Generative AI, NLP and diverse Deep Learning models that are compliant with the Bank's internal Model Risk Policy, adhere with industry and academic best practices, and meet regulatory requirements.
• Respond to requests from both Canadian and U.S. regulators, internal and external audit in their review/audit of models and vetting/validation process and procedures. Provide information and assistance as required.
• Work effectively with internal Model Development groups, Audit, and other internal partners to ensure models meet required Bank standards for use.
• Play a key role in ensuring the appropriate use of AI/ML models. Identify the need to implement new models/techniques as industry standards evolve and regulatory requirements change.
• Maintain full professional knowledge of techniques and developments in the field of AI and Machine Learning, and share knowledge with business partners and senior management. Provide subject matter expertise to business units on Generative AI, LLMs / NLP and other Deep Learning modeling and validation.
• Stay up to date with advancements in the field of Generative AI including major publications, important Large Language Models (LLMs), evaluation metrics, technology stacks, and datasets.
• Communicate findings and recommendations to both technical and non-technical stakeholders.

The position involves working effectively with internal partners from different model development groups and other relevant 2nd line risk control functions.

* Job Requirements

• Advanced quantitative and AI / ML skills with post-secondary degree in one or more of the following areas: computer science, machine learning / AI, engineering, statistics, mathematics, etc.
• 4+ years of experience in either developing or validating Generative AI, LLMs, NLP and other Deep Learning models; and 2+ years of experience in leading a small team of machine learning scientists.
• In-depth knowledge of AI/ML methodologies, concepts and theory including Generative AI, Deep Learning, modern Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG), Transformers, Diffusion models, and etc.
• Experience with Deep Learning and Generative AI technology stacks and libraries such as PyTorch, PromptFlow, LangChain, HuggingFace, etc.
• Motivated to stay up to date with the latest advancements in Generative AI, machine learning, and cloud technologies.
• Proficient in one or more scripting/programming languages such as Python.
• Familiarity with cloud platforms (e.g., Azure, AWS) and big data technologies (e.g., PySpark, Hadoop).
• 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. and stakeholder management abilities (position requires writing and reviewing reports of technical nature).
• Strong critical and analytic thinking skills.
• Excellent time / project management and multitasking skills with minimal supervision.
• 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 and research in GenAI/LLM field is a plus.
• Ability to implement AI/ML algorithms from academic research papers is a plus.

Aperçu du département

Le groupe de Validation des Modèles (Model Validation - MV) est une fonction centralisée de gestion du risque de modèles au sein de la Banque. Il a connu une forte croissance au cours des dernières années, reflétant l'attention accrue des régulateurs mondiaux sur le risque de modèles.
Le groupe de Validation des Modèles d'Intelligence Artificielle et d'Apprentissage Automatique (IA/AA - AI/ML MV) est responsable de l'examen, de l'évaluation et de l'approbation des modèles IA/AA développés et utilisés dans l'ensemble de l'entreprise (ex. : Lutte contre la fraude, Risque de crédit au détail, Marketing, NLP, TD Wealth, TD Asset Management, Gestion du bilan, TD Assurance, TD Valeurs Mobilières), y compris les modèles d'IA générative et d'autres modèles contemporains d'apprentissage profond.

Description du poste

Le poste relève du vice-président adjoint (VPA) du groupe de validation des modèles IA/AA et est principalement axé sur la direction de l'équipe responsable de l'examen et de la validation des modèles d'IA générative, de NLP et d'autres modèles d'apprentissage profond.

Responsabilités détaillées :

• Diriger la R&D dans les domaines de l'évaluation et des tests des modèles GenAI/Agentiques/LLM.
• Diriger une équipe de scientifiques en apprentissage automatique chargés de valider des modèles IA/AA complexes, notamment les modèles d'IA générative, LLM/NLP et d'apprentissage profond.
• Valider (examiner, tester/évaluer et effectuer un défi constructif auprès des développeurs) les modèles IA/AA, en particulier les modèles génératifs et d'apprentissage profond.
• Recommander l'approbation des modèles ou proposer des mesures correctives a la suite de la validation indépendante.
• Diriger et soutenir une équipe de validateurs de modèles.
• Définir les objectifs de performance pour tout le personnel et fournir des rétroactions régulières.
• Communiquer les objectifs et stratégies du groupe et aligner les activités avec les objectifs d'affaires.
• Soutenir le développement des employés, coacher et accompagner les membres de l'équipe dans l'atteinte de leurs objectifs professionnels.
• Assumer un rôle de leadership dans l'élaboration de normes et procédures pour la validation des modèles d'IA générative, de NLP et d'apprentissage profond, conformes a la politique interne de gestion du risque de modèles, aux meilleures pratiques industrielles et académiques, et aux exigences réglementaires.
• Répondre aux demandes des régulateurs canadiens et américains, ainsi que des auditeurs internes et externes, concernant l'examen des modèles et les processus/procédures de validation. Fournir l'information et l'aide nécessaires.
• Collaborer efficacement avec les équipes internes de développement de modèles, l'audit et d'autres partenaires internes afin de s'assurer que les modèles répondent aux normes requises pour leur utilisation au sein de la Banque.
• Jouer un rôle clé dans l'assurance d'une utilisation appropriée des modèles IA/AA. Identifier la nécessité d'implanter de nouveaux modèles/techniques a mesure que les normes industrielles évoluent et que les exigences réglementaires changent.
• Maintenir une expertise approfondie des techniques et avancées en IA et en apprentissage automatique, et partager les connaissances avec les partenaires d'affaires et la haute direction. Agir en tant qu'expert en la matière pour les unités d'affaires sur l'IA générative, les LLM/NLP et les modèles d'apprentissage profond.
• Rester a jour sur les avancées en IA générative, y compris les publications majeures, les modèles de langage (LLM) importants, les métriques d'évaluation, les piles technologiques et les jeux de données.
• Communiquer les conclusions et recommandations aux parties prenantes techniques et non techniques.
• Travailler efficacement avec les partenaires internes provenant de différents groupes de développement de modèles et des fonctions de contrôle du risque de deuxième ligne.

Exigences du poste

• Compétences avancées en quantitatif et en IA/AA, avec un diplôme postsecondaire en informatique, apprentissage automatique/IA, génie, statistiques, mathématiques, etc.
• Plus de 4 ans d'expérience dans le développement ou la validation de modèles d'IA générative, LLM, NLP et d'apprentissage profond; et plus de 2 ans d'expérience dans la direction d'une petite équipe de scientifiques en apprentissage automatique.
• Connaissance approfondie des méthodologies, concepts et théories IA/AA, incluant IA générative, apprentissage profond, NLP moderne, RAG, Transformers, modèles de diffusion, etc.
• Expérience avec les piles technologiques et bibliothèques d'apprentissage profond et d'IA générative telles que PyTorch, PromptFlow, LangChain, HuggingFace, etc.
• Motivation a demeurer informé des dernières avancées en IA générative, apprentissage automatique et technologies infonuagiques.
• Maîtrise d'un ou plusieurs langages de programmation/scripting (ex. : Python).
• Familiarité avec les plateformes infonuagiques (ex. : Azure, AWS) et les technologies Big Data (ex. : PySpark, Hadoop).
• Connaissance des structures de données, de la conception d'algorithmes et des principes de la programmation orientée objet (POO).
• Connaissance des algorithmes d'explicabilité/interprétabilité des modèles ML.
• Excellentes compétences de communication orale et écrite, ainsi que des aptitudes en gestion des parties prenantes (le poste implique la rédaction et la révision de rapports techniques).
• Solides compétences d'analyse et de pensée critique.
• Excellentes compétences en gestion du temps/projets, capacité a gérer plusieurs tâches avec un minimum de supervision.
• Capacité a travailler de manière autonome et collaborative dans un environnement dynamique et rapide.

Qualifications souhaitées

• Publications dans des conférences ou revues pertinentes, et recherches dans le domaine GenAI/LLM (un atout).
• Capacité a implémenter des algorithmes IA/AA a partir d'articles de recherche académiques (un atout).

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 deliver legendary customer experiences to 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 the Bank, those we serve, and the economies we support. We are guided by our vision to Be the Better Bank and our purpose to enrich the lives of our customers, communities and colleagues.

TD is deeply committed to being a leader in customer experience, that is why we believe that all colleagues, no matter where they work, are customer facing. As we build our business and deliver on our strategy, we are innovating to enhance the customer experience and build capabilities to shape the future of banking. Whether you've got years of banking experience or are just starting your career in financial services, we can help you realize your potential. Through regular leadership and development conversations to mentorship and training programs, we're here to support you towards your goals. As an organization, we keep growing - and so will you.

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. Whether you have a passion for helping customers and want to expand your experience, or you want to coach and inspire your colleagues, there are many different career paths within our organization at TD - and we're committed to helping you identify opportunities that support your goals.

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