Full-time jobs in Canada (397,205 jobs)

Explore full-time jobs across Canada. Choose a location and read the full job details.

397,205 listings · 48,050 employers Counted Nov 13, 2026. How we count

About these jobs

Employers hiring include Walmart Canada (9,524 listings), Health Match BC (4,401 listings), Walmart (3,041 listings).

Common roles: Project manager, Sales representative, Store manager.

68,697 of these listings include employer-provided pay. Open a job to see its currency and pay period.

Advertised starting pay
Pay period	Median starting pay	Listings
CAD / hour	24.00	39,693
CAD / year	80,000.00	26,612
CAD / month	5,317.00	727
USD / year	125,000.00	231
CAD / week	1,635.30	87
CAD / day	360.00	44
USD / hour	22.00	29
GBP / year	40,000.00	13
EUR / year	68,000.00	11
USD / month	4,000.00	11

Employer-listed minimums from at least 10 listings per currency and pay period. These are advertised starting amounts, not employee salaries. Jobs without a minimum and unusual amounts are excluded.

Workplace classifications: 1% remote, 16% hybrid, 82% on-site, 0% not specified. Hybrid and on-site classifications may be inferred from descriptions. Check the original ad.

Based on the dated count above. Listings can change. How we count

Full-time jobs in Canada

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Inverted AI

Software Engineer - ML Training & Onboard Autonomy

Vancouver, BC, Canada

Full-time

Apply on LinkedIn About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: May 11, 2027
Posting language: English
Posted: Nov 12, 2026

Original job description

Inverted AI is a Vancouver-based UBC spin-out building the behaviour models behind autonomous driving. Our generative models of human driving are used by AV and ADAS companies for simulation, and we now train and deploy end-to-end driving policies that run onboard real vehicles. We have a large proprietary drone-captured driving dataset, abundant GPU compute, and a small, technically dense team of researchers and engineers.

The role

We are hiring software engineers who have already taken learned models from a training cluster onto a real robot or vehicle. You will own large parts of the path from data to deployed policy: training and evaluating driving policy and perception models, then making them run reliably, in real time, on embedded compute in our test vehicles. You'll work directly with our researchers and have substantial ownership from day one.

What you'll do

Train, debug and evaluate end-to-end driving policy and perception models (PyTorch) on multi-GPU clusters
Build and maintain data pipelines that turn raw video, CAN and sensor logs into training data
Export, quantize and optimize models for embedded GPUs/accelerators (e.g. ONNX, TensorRT or similar) and hit real-time latency budgets
Integrate models with the vehicle software stack (ROS 2 / C++ nodes, sensor drivers, vehicle interfaces) and support on-vehicle testing
Build closed-loop simulation and evaluation tooling that predicts on-road behaviour
Keep our Python and C++ codebases, containers (Docker/Singularity) and CI healthy

Required qualifications

BSc or MSc in Computer Science, Computer Engineering, Engineering Physics or similar
2+ years (industry, or substantial graduate research/co-op) building ML or robotics systems
Hands-on experience deploying a learned model onboard a real robot, vehicle or drone, not only in simulation
Hands-on experience training deep learning models in PyTorch, including debugging training runs
Strong Python and solid modern C++; comfortable on Linux with git and Docker
Able to work without a rigidly defined scope and to own problems end to end

Nice to have

Autonomous driving, ADAS or mobile robotics industry experience
ROS 2, NVIDIA Jetson/DRIVE, AMD or other embedded accelerator experience; TensorRT/ONNX Runtime
Reinforcement learning, imitation learning or behaviour cloning for control; diffusion or flow-based generative models
CAN bus, vehicle interfaces, sensor calibration or time synchronization
Real-time / safety-conscious systems engineering

What we offer

Salary: $90,000 - $120,000 CAD per year, depending on experience, plus participation in our employee stock option plan
Health and wellness benefits and paid time off
Your code runs on real vehicles, not just in benchmarks
A small, fast-moving team with direct access to world-class ML researchers

Hiring process

A 30-minute remote screen with a short coding exercise; a 1-2 hour in-depth interview (in person if you're in Vancouver); a take-home with a programming and a design part, completed within a 48-hour window; then reference checks.

In person, downtown Vancouver, BC. Full-time. Must be legally entitled to work in Canada. Inverted AI is an equal opportunity employer. We welcome applicants from all backgrounds and make hiring decisions on qualifications, merit and business needs.

Apply on LinkedIn About employer

More about this job

Responsibilities

Train, debug, and evaluate driving policy and perception models, and build data pipelines from video, CAN, and sensor logs. Optimize and integrate models for real-time operation on embedded vehicle hardware, while developing simulation and evaluation tools and maintaining the Python and C++ codebases, containers, and CI.

Requirements

Requires a BSc or MSc in a relevant technical field, at least two years of experience building ML or robotics systems, and hands-on experience training PyTorch models and deploying learned models on a real robot, vehicle, or drone. Candidates need strong Python, solid modern C++, Linux, Git, and Docker skills, along with the ability to own problems end to end.

Skills

PyTorch
Python
C++
Machine Learning
Deep Learning
Robotics
Autonomous Driving
Model Deployment
Embedded Systems
ONNX
TensorRT
ROS 2
Docker
Linux
Multi-GPU Training
Data Pipelines

Benefits

Employee Stock Options
Health And Wellness Benefits
Paid Time Off

Visa sponsorship

Not detected in the job text

Keywords

Autonomous Driving
Advanced Driver Assistance Systems
Machine Learning
Deep Learning
PyTorch
Python
C++
Robotics
End-To-End Driving Policies
Perception Models
Multi-GPU Clusters
Training Data
Video Data
CAN Bus
Sensor Logs
Embedded GPUs
Embedded Accelerators
ONNX
TensorRT
ROS 2
Vehicle Software Stack
Sensor Drivers
Vehicle Interfaces
Closed-Loop Simulation
Docker
Singularity
Continuous Integration
Reinforcement Learning
Imitation Learning
Behaviour Cloning

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Work requirements

Full-time jobs in Canada