“Senior Applied Machine Learning Scientist, Generative AI “
Full time @TD BANK posted 6 hours ago in Accounting / Finance Shortlist Email JobJob Detail
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Job ID 20221
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Experience 4 Years
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Qualifications Degree Bachelor
Job Description
“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 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.
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 is a plus.
Ability to implement AI/ML algorithms from academic research papers is a plus.
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Required skills
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