Work Location:
Montreal, 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.
Apercu du departement
Le groupe de Validation des Modeles (Model Validation - MV) est une fonction centralisee de gestion du risque de modeles au sein de la Banque. Il a connu une forte croissance au cours des dernieres annees, refletant l'attention accrue des regulateurs mondiaux sur le risque de modeles.
Le groupe de Validation des Modeles d'Intelligence Artificielle et d'Apprentissage Automatique (IA/AA - AI/ML MV) est responsable de l'examen, de l'evaluation et de l'approbation des modeles IA/AA developpes et utilises dans l'ensemble de l'entreprise (ex. : Lutte contre la fraude, Risque de credit au detail, Marketing, NLP, TD Wealth, TD Asset Management, Gestion du bilan, TD Assurance, TD Valeurs Mobilieres), y compris les modeles d'IA generative et d'autres modeles contemporains d'apprentissage profond.
Description du poste
Le poste releve du vice-president adjoint (VPA) du groupe de validation des modeles IA/AA et est principalement axe sur la direction de l'equipe responsable de l'examen et de la validation des modeles d'IA generative, de NLP et d'autres modeles d'apprentissage profond.
Responsabilites detaillees :
• Diriger la R&D dans les domaines de l'evaluation et des tests des modeles GenAI/Agentiques/LLM.
• Diriger une equipe de scientifiques en apprentissage automatique charges de valider des modeles IA/AA complexes, notamment les modeles d'IA generative, LLM/NLP et d'apprentissage profond.
• Valider (examiner, tester/evaluer et effectuer un defi constructif aupres des developpeurs) les modeles IA/AA, en particulier les modeles generatifs et d'apprentissage profond.
• Recommander l'approbation des modeles ou proposer des mesures correctives a la suite de la validation independante.
• Diriger et soutenir une equipe de validateurs de modeles.
• Definir les objectifs de performance pour tout le personnel et fournir des retroactions regulieres.
• Communiquer les objectifs et strategies du groupe et aligner les activites avec les objectifs d'affaires.
• Soutenir le developpement des employes, coacher et accompagner les membres de l'equipe dans l'atteinte de leurs objectifs professionnels.
• Assumer un role de leadership dans l'elaboration de normes et procedures pour la validation des modeles d'IA generative, de NLP et d'apprentissage profond, conformes a la politique interne de gestion du risque de modeles, aux meilleures pratiques industrielles et academiques, et aux exigences reglementaires.
• Repondre aux demandes des regulateurs canadiens et americains, ainsi que des auditeurs internes et externes, concernant l'examen des modeles et les processus/procedures de validation. Fournir l'information et l'aide necessaires.
• Collaborer efficacement avec les equipes internes de developpement de modeles, l'audit et d'autres partenaires internes afin de s'assurer que les modeles repondent aux normes requises pour leur utilisation au sein de la Banque.
• Jouer un role cle dans l'assurance d'une utilisation appropriee des modeles IA/AA. Identifier la necessite d'implanter de nouveaux modeles/techniques a mesure que les normes industrielles evoluent et que les exigences reglementaires changent.
• Maintenir une expertise approfondie des techniques et avancees 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 matiere pour les unites d'affaires sur l'IA generative, les LLM/NLP et les modeles d'apprentissage profond.
• Rester a jour sur les avancees en IA generative, y compris les publications majeures, les modeles de langage (LLM) importants, les metriques d'evaluation, les piles technologiques et les jeux de donnees.
• Communiquer les conclusions et recommandations aux parties prenantes techniques et non techniques.
• Travailler efficacement avec les partenaires internes provenant de differents groupes de developpement de modeles et des fonctions de controle du risque de deuxieme ligne.
Exigences du poste
• Competences avancees en quantitatif et en IA/AA, avec un diplome postsecondaire en informatique, apprentissage automatique/IA, genie, statistiques, mathematiques, etc.
• Plus de 4 ans d'experience dans le developpement ou la validation de modeles d'IA generative, LLM, NLP et d'apprentissage profond; et plus de 2 ans d'experience dans la direction d'une petite equipe de scientifiques en apprentissage automatique.
• Connaissance approfondie des methodologies, concepts et theories IA/AA, incluant IA generative, apprentissage profond, NLP moderne, RAG, Transformers, modeles de diffusion, etc.
• Experience avec les piles technologiques et bibliotheques d'apprentissage profond et d'IA generative telles que PyTorch, PromptFlow, LangChain, HuggingFace, etc.
• Motivation a demeurer informe des dernieres avancees en IA generative, apprentissage automatique et technologies infonuagiques.
• Maitrise d'un ou plusieurs langages de programmation/scripting (ex. : Python).
• Familiarite avec les plateformes infonuagiques (ex. : Azure, AWS) et les technologies Big Data (ex. : PySpark, Hadoop).
• Connaissance des structures de donnees, de la conception d'algorithmes et des principes de la programmation orientee objet (POO).
• Connaissance des algorithmes d'explicabilite/interpretabilite des modeles ML.
• Excellentes competences de communication orale et ecrite, ainsi que des aptitudes en gestion des parties prenantes (le poste implique la redaction et la revision de rapports techniques).
• Solides competences d'analyse et de pensee critique.
• Excellentes competences en gestion du temps/projets, capacite a gerer plusieurs taches avec un minimum de supervision.
• Capacite a travailler de maniere autonome et collaborative dans un environnement dynamique et rapide.
Qualifications souhaitees
• Publications dans des conferences ou revues pertinentes, et recherches dans le domaine GenAI/LLM (un atout).
• Capacite a implementer des algorithmes IA/AA a partir d'articles de recherche academiques (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:
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