AI role · Open offer

ML Engineer — autonomous driving perception

Waabi

Full-time
Senior
Perception
Hybrid
Toronto, ON, Canada · Hybrid
Toronto, Canada
CAD 150k–200k/year + equity

This listing is optimized for AI-native talent: clear skills and tools so candidates know if they fit before they apply—and so you spend less time screening mismatches.

4 skills2 tools

At a glance

How you'll work, where, and key listing dates.

Employment: Full-time
Workplace: Hybrid
Location: Toronto, ON, Canada · Hybrid
Compensation: CAD 150k–200k/year + equity
Experience level: Senior
Team: Perception
Benefits & perks

About this role

What the team is looking for and how this position fits.

Waabi is hiring a Senior ML Engineer — autonomous driving perception on the Perception team (Hybrid · Toronto, Canada). This is a hands-on role in computer vision & geospatial AI—not a generic “AI enthusiast” post.

You will own vision, sensor, or geospatial models in production end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.

Waabi builds autonomous trucking AI from Toronto — Waabi careers for perception and simulation ML.

ML Engineer (hybrid Toronto): 3D perception, simulation, and robust autonomy models.

Missions

Improve perception models with closed-loop evaluation.
Collaborate with simulation on data and metrics.

Stack & environment

Python, PyTorch, CUDA, Docker.

What we look for

CV/autonomy ML; Canada work auth.

Skills we're hiring for

What each capability means for this role—not a keyword checklist.

Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
PyTorch
Training and inference with PyTorch: reproducible experiments, checkpointing, and deployment-minded exports.
Computer Vision

Tools & stack

Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).

DockerTool
Containerized services and reproducible dev environments for ML and LLM workloads.
CUDATool
Regular use of CUDA in the computer vision & geospatial AI stack—configuration, debugging, and team conventions.

You're a strong fit if…

Tailored to this listing—use it as a self-check before you apply.

You can show evidence in your application: 3D perception, simulation ML, or autonomy stacks.
Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, Computer Vision, Machine Learning, and Docker.
You have owned vision, sensor, or geospatial models in production in production: debugging live issues, running postmortems, and iterating from real user or business signals.
You are comfortable with the hybrid rhythm (Hybrid · Toronto, Canada)—onsite collaboration when it matters, deep work when remote.
You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.
You read the full listing (comp: CAD 150k–200k/year + equity, benefits in At a glance) and your expectations align.

Apply

Candidate accounts only: add your headline and bio on , and optionally a CV link or PDF so recruiters see your full résumé. Then write a short pitch below—applications use your login email.

What the employer asked for

3D perception, simulation ML, or autonomy stacks.

Register, add a headline and bio, then you can attach a CV link or PDF on My account before you apply. That keeps applications tied to your profile and makes it easier for employers to review your background.

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