Senior Machine Learning Engineer in Toronto

As one of the world’s top three credit ratings agencies, Fitch Ratings plays a critical role in global capital markets by providing credit analysis, ratings, research, and commentary to financial market participants. For over 100 years, Fitch Ratings has been creating value for global markets through its rigorous analysis and deep expertise.

Join our fast‑growing Toronto innovation hub, where we’re building production‑grade AI to reshape global credit decisions. Here, you won’t just ship features—you’ll help reinvent an industry using decades‑deep proprietary data and a modern tech stack, free from heavy legacy. Backed by full enterprise support, you’ll build reliable, explainable intelligence at real scale within a collaborative, outcome‑driven community.

Fitch Ratings is seeking a Senior Machine Learning Engineer to join our new AI Innovation teams in Toronto—where we're building the AI‑powered future of financial analysis from the ground up. This isn't about tweaking hyperparameters or maintaining legacy models. This is about designing and shipping breakthrough generative AI systems, agentic workflows, and intelligent platforms that will transform how credit analysis happens and how global financial markets operate.

We're at a defining moment. Fitch is making a major strategic bet on AI, investing heavily in Toronto as our innovation center, and we're building teams of exceptional ML engineers to turn ambitious vision into production reality. As a Senior ML Engineer, you'll be a technical force on the team—building sophisticated ML systems, driving innovation through hands‑on work, mentoring engineers, and helping establish the technical standards that will scale across the organization.

We need ML engineers who thrive on hard problems and greenfield opportunities—whether you're passionate about pushing the boundaries of what LLMs can do, excited to architect intelligent systems that reason and act, or energized by turning cutting‑edge research into production capabilities. If you're motivated by "let's build this and see what's possible" rather than "let's wait and see what others do," this is a high‑impact role where you'll spend your time shipping transformative ML systems—working alongside talented engineers who are equally committed to building something significant.

What We Offer:

• Build breakthrough ML systems with real impact– Design and ship production generative AI platforms, multi‑agent systems, and intelligent automation that will process billions in credit decisions.
• Work at the cutting edge of ML technology– Experiment with the latest LLMs and foundation models, implement novel RAG architectures, and leverage enterprise‑scale GPU clusters and cloud infrastructure.
• Technical leadership without the bureaucracy– Lead projects, mentor junior engineers, shape technical direction, and influence architectural decisions through your expertise and results.
• Toronto's world‑class AI ecosystem– Work in one of the world's premier AI research hubs alongside Vector Institute researchers.
• Greenfield innovation with enterprise backing– Build net‑new ML systems from scratch with the freedom to experiment boldly.
• Solve sophisticated ML challenges– Tackle hard problems at the intersection of NLP, document intelligence, reasoning systems, and production‑scale deployment.
• Clear growth trajectory– High visibility to senior leadership, mentorship from experienced ML architects, and clear paths to Lead ML Engineer or Principal ML Engineer roles.

We'll Count on You To:

• Design and build transformative ML systems– Lead the development of advanced generative AI solutions and intelligent platforms using PyTorch and modern ML frameworks.
• Drive AI innovation through hands‑on technical work– Experiment with frontier models, implement novel ML architectures, and translate cutting‑edge research into production capabilities.
• Lead projects and drive technical excellence– Take ownership of significant ML initiatives from design through deployment.
• Mentor and elevate junior engineers– Provide technical guidance, conduct code reviews, and foster a culture of learning.
• Build production ML infrastructure– Develop scalable APIs for model deployment and implement MLOps pipelines.
• Champion ML governance and operational excellence– Ensure adherence to AI/ML governance guidelines and optimize systems for reliability.
• Collaborate across teams effectively– Partner with product squads and cross‑functional teams to integrate ML solutions.

What You Need to Have:

• Strong ML engineering expertise– 6+ years of professional experience building production AI/ML systems.
• Advanced generative AI and LLM experience– Extensive hands‑on experience developing and integrating generative AI solutions.
• Deep ML technical skills– Strong proficiency in Python and ML algorithms.
• Bachelor's degree in Machine Learning, Computer Science, Data Science, Applied Mathematics, or related field (Master's or PhD is strongly preferred).
• Production ML engineering excellence– Strong understanding of MLOps, containerization, and cloud platforms.
• Software development fundamentals– Deep understanding of automated testing and source version control.
• Technical leadership through influence– Track record of leading project initiatives and mentoring team members.
• Outstanding collaboration and communication– Ability to work effectively with technical and non‑technical stakeholders.

What Would Make You Stand Out:

• Cutting‑edge AI implementation experience– Track record of taking breakthrough AI capabilities from research to production‑scale deployment.
• Multi‑agent and agentic systems expertise– Hands‑on experience building sophisticated multi‑agent systems.
• MLOps and cloud‑native infrastructure– Advanced expertise building ML infrastructure and optimizing cost/performance.
• Document and content management systems experience– Experience developing or integrating ML functionality for document management systems.
• Technical thought leadership– Contributions to open source ML projects or active participation in the ML engineering community.
• Financial services or analytical domain knowledge– Understanding of credit analysis workflows and regulatory requirements.
• Startup or innovation environment experience– History of building greenfield ML products.
• Toronto AI/ML community involvement– Active participation in Toronto's AI/ML engineering or research communities.

If you're ready to build transformative ML systems with organizational backing, cutting‑edge technology, and talented colleagues—this is the moment to join us.

Why Fitch? At Fitch Group, the combined power of our global perspectives is what differentiates us. Our global network of colleagues comes together to accomplish things greater than they ever could alone.

Every team member is essential to our business, and each perspective is critical to our success. We embrace a diverse culture that encourages a free exchange of ideas, guaranteeing your voice will be heard and your work will have an impact, regardless of seniority.

We are building incredible things at Fitch and we invite you to join us on our journey.