AI Engineer — Junior (BC)

The short version — Canada Quant Labs is hiring a junior AI Engineer. Open to anyone early in their career — self-taught developers, bootcamp grads, career-switchers, new grads — who is based in British Columbia and able to work from our Victoria, BC office (hybrid). No degree, enrollment, or prior industry experience required — we hire for passion, personal projects, and demonstrated curiosity, not credentials. Full-time, permanent. CAD $85,000–$115,000 + equity.

The role

We're Canada's open-weight model lab: we train, quantize, and deploy sovereign AI on Canadian Blackwell silicon — and everything we ship is public: weights, recipes, benchmarks, and the engineering log of what broke along the way. Our Hugging Face org is the resume.

This posting is for engineers early in their careers in British Columbia: self-taught developers, bootcamp grads, career-switchers, and new grads alike. You don't need a degree or industry experience — most of what we do isn't taught anywhere anyway. You need curiosity about how these models actually work and the patience to measure things properly. We'll teach you the rest, and you'll be mentored directly by the senior engineers who built the pipeline.

What you'll work on

Real work, not busywork. Junior engineers here ship artifacts that go out under their own names:

• Quantization eval harnesses — run W4A16 and NVFP4 quants through reasoning, instruction-following, and long-context evals, and turn the results into the go/no-go evidence for what ships.
• Dataset pipelines — build, clean, and decontaminate the Canadian-corpora training and eval data (legal, medical, finance) that our domain models depend on.
• Inference benchmarks — throughput and latency profiles of vLLM serving on our DGX B300 capacity: reproduce published numbers, find where they break, document why.
• Model cards and engineering logs — write up what you measured. Our work is open by default; the write-up is part of the artifact, and your name goes on it.

What you bring

• You're early in your career and based in British Columbia — self-taught, bootcamp grad, career-switcher, or new grad. No degree, enrollment, or prior industry experience required: show us the repos.
• Solid Python. You can write a script that chews through 2 GB of logs without being told how, and you know what a virtualenv is.
• PyTorch is a plus — personal projects or coursework touching transformers or LLMs are even better, but neither is required.
• Genuine curiosity about open-weight models, quantization, and inference. You've read a model card for fun, or run a 7B on your own GPU just to see what happens.
• You can work from our Victoria, BC office (hybrid — some days remote, some days in the room with us).

Nice to have

• Personal projects with artifacts — a trained model, a benchmark, a tool other people use.
• Kaggle competitions, hackathons, CTFs — anything with a scoreboard.
• Open-source contributions, however small — a merged typo PR still tells us you can navigate a strange codebase.
• A blog or write-ups about something you built or measured.

Logistics

How to apply

Apply below — a résumé and links to things you've built are all we need. No cover letter required; the note field is a few sentences about why CQL, not an essay.

We read every application and reply within two weeks. The process: intro call → technical chat about a project you're proud of → offer.