Senior Machine Learning Engineer - AI InnovationTeams

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alert : Requisition ID :

49271

Business Unit : Fitch

Group

Category : Information

Technology

Location : Toronto, ON,

Date Posted : Jan 13,

2026

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. You're

joining early enough to shape how we build, with the resources and

runway to do it right.

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 on problems at the frontier of

applied AI while seeing your work directly change how analysts and

financial markets operate

Work at the cutting

edge of ML technology – Experiment with the latest LLMs and

foundation models, implement novel RAG architectures, build agentic

systems, fine‑tune neural networks, and leverage enterprise‑scale

GPU clusters and cloud infrastructure; substantial conference and

training budgets to stay at the

forefront

Technical leadership without the

bureaucracy – Lead projects, mentor junior engineers, shape

technical direction, and influence architectural decisions through

your expertise and results—not through management hierarchy; your

ideas and code will define how we build AI

systems

Toronto's world‑class AI ecosystem –

Work in one of the world's premier AI research hubs alongside

Vector Institute researchers, attend cutting‑edge ML meetups and

conferences, and be part of the community defining the future of

applied AI and machine learning

Greenfield

innovation with enterprise backing – Build net‑new ML systems from

scratch with the freedom to experiment boldly, fail fast, and push

boundaries—backed by the compute resources, research budgets, and

organizational support that most startups can only dream

Solve sophisticated ML challenges – Tackle

hard problems at the intersection of NLP, document intelligence,

reasoning systems, agentic workflows, and production‑scale

deployment; work on challenges that will expand your expertise and

push your technical boundaries

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; build a reputation as a go‑to expert

in generative AI and financial

technology

We'll Count on You

To :

Design and build transformative ML systems

Lead the development of advanced generative AI solutions, agentic

workflows, RAG architectures, and intelligent platforms using

PyTorch, modern ML frameworks, and large language models; write

production‑quality code that scales and

performs

Drive AI innovation through hands‑on

technical work – Experiment with frontier models, implement novel

ML architectures, evaluate emerging AI technologies, build

proofs‑of‑concept, and translate cutting‑edge research into

production capabilities that deliver real business

value

Lead projects and drive technical

excellence – Take ownership of significant ML initiatives from

design through deployment; make architectural decisions, establish

coding standards, implement robust CI / CD for ML systems, and ensure

solutions are both innovative and

reliable

Mentor and elevate junior engineers –

Provide technical guidance, conduct code reviews, share ML best

practices, and help junior team members grow their skills; foster a

culture of learning, experimentation, and