Work Location:Toronto, Ontario, Canada
Hours:37.5
Line of Business:Analytics, Insights, & Artificial Intelligence
Pay Details:$105,500 - $134,500 CAD
The pay details posted reflect a temporary market premium specific to this role that is reassessed annually.
Job Description:*Department OverviewTD 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 DescriptionThe 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.
Our Total Rewards PackageOur 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.
If you're passionate about helping clients and building deep, lasting relationships, TD offers diverse career paths where you can grow your expertise and make a meaningful impact.
We're committed to your success and foster a respectful workplace where diverse perspectives are valued, everyone has fair opportunities to grow, and you can unlock your full potential to achieve your career goals. Here at TD, we hire and develop the best.
Training & OnboardingWe 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
