Senior Applied Machine Learning Scientist, Generative AI Model Validation ATH# 5480

Work Location: Montréal, Quebec, Canada Hours: 37.5 Line of Business: Analytics, Insights, & Artificial Intelligence Pay Details: $156,500 - $90,000 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 (AI) Model Validation (MV) group is responsible for the review/vetting and approval of AI 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 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/review of complex AI models, particularly Generative AI, LLMs / NLP and Deep Learning models. Validate (review, test/evaluate, and provide effective challenge to the model developers) AI models, particularly Generative AI and Agentic models. Recommend the approval of models or other corrective actions based on an 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, Agentic AI 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 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, Agentic 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 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 methodologies, concepts and theory including Generative AI, Agentic AI, Deep Learning, modern Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG), Transformers, and etc. Experience with Deep Learning and Generative AI / Agentic AI technology stacks and libraries such as PyTorch, LangChain, LangGraph, HuggingFace, etc. Motivated to stay up to date with the latest advancements in Generative AI, Agentic 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 algorithms from academic research papers is a plus. *Aperçu du service Le groupe Validation des modèles est une fonction centralisée de Gestion des risques de modèle au sein de la Banque. Il a connu une croissance rapide au cours des dernières années, grâce à l’attention croissante des organismes de réglementation mondiaux à l’égard du risque de modèle. Le groupe Validation des modèles, Intelligence artificielle (IA) est responsable de l’examen, de la vérification et de l’approbation des modèles d’IA élaborés et utilisés à l’échelle de l’entreprise (p. ex., Fraude, Risque de crédit de détail, Marketing, Traitement du langage naturel, Gestion de patrimoine TD, Gestion de Placements TD, Gestion de la trésorerie et du bilan, TD Assurance, Valeurs mobilières TD) y compris l’IA générative et d’autres modèles modernes d’apprentissage profond. *Description de poste Le ou la titulaire du poste relèvera du vice-président associé, groupe Validation des modèles, IA et AA et se concentrera principalement sur la validation des modèles d’IA générative et d’apprentissage profond. Voici les responsabilités détaillées du poste : Diriger la recherche et le développement dans les domaines de l’évaluation et des tests de GenAI, Agentic et LLM. Diriger l’équipe de scientifiques spécialisés dans l’AA afin d’effectuer la validation de tous les modèles d’IA, particulièrement les modèles d’IA générative/agentic, grands modèles de langage/traitement du langage naturel et d’apprentissage profond. Valider (examiner, tester et effectuer un examen critique efficace aux développeurs de modèles) les modèles d’intelligence artificielle et d’apprentissage automatique, en particulier les modèles d’intelligence artificielle générative et d’apprentissage profond. Recommander l’approbation des modèles ou d’autres mesures correctives en fonction