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Urban Ridge Supplies

Software Engineer III (AI Integration)

Toronto, ON, Canada

Pay: $125,500 - $154,000 CAD
Job type: Full-time
Experience: 7 years relevant experience
Posting language: English
Posted: Sep 24, 2026

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Original job description

Work Location:

Toronto, Ontario, Canada

Hours

37.5

Line Of Business

Technology Solutions

Pay Details

$125,500 - $154,000 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

The AI Engineer is responsible for designing, building, and deploying AI/ML solutions that enhance business processes, improve decision-making, and enable automation. This role combines software engineering, data science, and machine learning expertise to develop scalable AI systems in production environments.

Key Responsibilities

Develop end-to-end pipelines including data preprocessing, feature engineering, validation, and deployment.
Fine-tune LLM-based applications using frameworks like LangChain, LangSmith, or OpenAI APIs.
Deploy models into production using CI/CD pipline.
Build scalable microservices or APIs to serve ML models in real time.
Implement monitoring for model drift, performance, and reliability.
Collaborate with data engineering teams to define data requirements.
Work with structured and unstructured datasets using Python, SQL, Spark, Pandas, etc.
Ensure data quality, governance, and security
Evaluate new AI frameworks, tools, and techniques.
Prototype solutions and run experiments to explore feasibility.
Stay up to date with advancements in LLMs, vector embeddings, multimodal AI, and model compression/optimization.
Work with product managers and business teams to translate business problems into AI solutions.
Partner with cloud engineers and DevOps teams for scalable deployment.
Communicate complex technical concepts to non-technical stakeholders.

Required Skills & Qualifications

7 years relevant experience
Strong programming skills in Python (NumPy, Pandas, Scikit-learn, PyTorch or TensorFlow).
Experience with LLMs, NLP, or deep learning.
Knowledge of MLOps tools: MLflow, Kubeflow, Airflow, Docker, Kubernetes.
Experience with cloud platforms (AWS/GCP/Azure) and model deployment.
Understanding of data structures, algorithms, and software engineering best practices.
Problem-solving and analytical thinking.
Ability to design scalable, maintainable systems.
Strong communication and documentation skills.
Collaboration in agile or cross-functional team environments.

Preferred Qualifications (Nice To Have)

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
Experience building large-scale AI systems or enterprise-grade ML applications.
Experience working in regulated industries.
Knowledge of vector databases , RAG systems, or generative AI applications.

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 strive to make every interaction, product, and experience remarkably human and refreshingly simple for 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 foster deeper relationships, ensure disciplined execution, and build a simpler, faster banking experience. TD is deeply committed to being a leader in client experience, that is why we believe that all colleagues, no matter where they work, are client facing. Together, we are reimagining what banking can be for our clients, colleagues and communities.

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.

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 & 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

Job Id: U/KA1ggkTajRpvIxusOozsj17dezeoOMjlQMVczZyX0OpSKBl7eKjNJUz+Cwoj/ZN22qB/xlbyNpM/suK2KsAoUqewyF/h41Pg==

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More about this job

Responsibilities

The AI Engineer is responsible for designing, building, and deploying scalable AI/ML solutions to enhance business processes and automation. This role involves developing end-to-end data pipelines, fine-tuning LLM-based applications, and collaborating with cross-functional teams to implement production-ready models.

Requirements

Candidates must have at least 7 years of relevant experience with strong programming skills in Python and experience in machine learning, NLP, or deep learning. Proficiency in MLOps tools, cloud platforms, and software engineering best practices is required to design and maintain scalable systems.

Skills

Python
Machine learning
LLMs
NLP
Deep learning
MLOps
Cloud platforms
Data engineering
Software engineering
CI/CD
Microservices
SQL
Spark
Pandas
PyTorch
TensorFlow

Benefits

Health and well-being benefits
Savings and retirement programs
Paid time off
Banking benefits and discounts
Career development
Reward and recognition programs

Visa sponsorship

Not detected in the job text

Keywords

Software Engineer
AI Integration
Machine Learning
Python
LLM
NLP
Deep Learning
MLOps
MLflow
Kubeflow
Airflow
Docker
Kubernetes
AWS
GCP
Azure
Data Engineering
CI/CD
Microservices
SQL
Spark
Pandas
PyTorch
TensorFlow
Vector Databases
RAG
Generative AI
Agile
Data Governance
Multimodal AI

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