Senior Machine Learning Engineer
TD Bank is hiring a Senior Machine Learning Engineer in Toronto, Canada. Level rates it ; you can apply on Level.
AI in this role
Work Location:
Toronto, Ontario, CanadaHours:
37.5Line of Business:
Analytics, Insights, & Artificial IntelligencePay Details:
$115,600 - $163,200 CADThis role is temporarily eligible for a pay premium above the posted salary range that is reassessed annually. You are encouraged to have an open dialogue with your recruiter who can provide more specific pay details for this role.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:
We are seeking a Senior AI/ML Engineer to drive the strategic implementation of generative AI and machine learning capabilities across TD's enterprise platforms. This individual contributor role combines deep technical expertise in large language models and cloud AI services with strategic thinking to architect and deliver production-scale AI solutions that transform how TD serves customers globally. You will be at the forefront of TD's AI transformation, working with cutting-edge technologies and enterprise LLM frameworks to solve complex business challenges while ensuring compliance with stringent banking regulations and responsible AI practices.
KEY ACCOUNTABILITIES
- Design and implement end-to-end generative AI solutions leveraging Azure AI and Google AI services to deliver transformative business changes and capabilities.
- Lead the development and optimization of production-grade LLM applications using advanced techniques including RAG (Retrieval Augmented Generation), prompt engineering, fine-tuning, and multi-agent architectures to achieve measurable business outcomes
- Implement AI security frameworks such as prompt injection, adversarial attack mitigation, data poisoning detection and prompt shield
- Deliver solutions for content filtering, output monitoring and automated safety guardrails for generative AI systems.
- Architect scalable MLOps pipelines and AIOps frameworks ensuring model versioning, automated retraining, monitoring, and explainability while maintaining 99.9% availability for mission-critical AI services
- Partner with business stakeholders to translate strategic objectives into AI/ML proof-of-concepts and production solutions, demonstrating clear ROI and business value through rapid prototyping and iterative development
- Drive technical strategy for expanding AI/ML capabilities across hybrid cloud landscape, evaluating emerging technologies including small language models, agentic AI, and edge deployment strategies
- Mentor platform engineers and data scientists on advanced ML techniques, LLMOps practices, and responsible AI principles through hands-on collaboration and technical leadership
- Conduct technical due diligence on AI vendors and tools, providing recommendations for strategic investments in technologies like Cohere, Anthropic, and open-source LLMs
EXPERIENCE & EDUCATION
- Bachelor's degree in Computer Science, Machine Learning, Mathematics, or related technical field
- Minimum 5+ years hands-on AI/ML engineering experience with 3+ years focused on generative AI and LLM applications
- 5+ years of executive leadership experience in financial services with proven ability to influence C-suite stakeholders and drive strategic technical initiatives
- Expert-level proficiency in Python, including ML frameworks (PyTorch/TensorFlow), LLM orchestration (LangChain/LlamaIndex).
- Deep hands-on experience with Azure OpenAI Service, Azure ML Studio, Databricks MLflow, and Google Vertex AI for enterprise-scale model deployment and management
- Strong understanding of MLOps/LLMOps practices including CI/CD for ML (Azure DevOps, GitHub Actions), infrastructure-as-code (Terraform), and containerization (Docker/Kubernetes)
- Experience with real-time ML inference, streaming architectures (Kafka/Pub/Sub), and edge deployment for latency-sensitive applications
- Hands-on experience with multi-modal models, computer vision, and advanced NLP beyond standard LLM 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 ObjetHow we rate this
Senior Machine Learning Engineer at TD Bank rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
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Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in machine learning engineer jobs at this level
Pay
- Typical machine learning engineer job
- $199k
This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
Adapt your resume
- List these exact terms on your resume: Prompt engineering, RAG, Fine-tuning, ML Ops, and Computer vision. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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