Jobs in Burnaby, BC and nearby

Jobs within 25 km of Burnaby, BC, Canada. Nearby towns and cities are included. Distances are straight-line, not driving distances.

42,202 listings · 7,543 employers Counted Nov 5, 2026. How we count

About these jobs

Employers hiring include Vancouver Coastal Health (1,246 listings), Health Match BC (1,094 listings), Fraser Health (932 listings).

Common roles: Retail sales associate, Registered nurse, Family physician.

10,675 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	32.84	6,714
CAD / year	80,000.00	3,309
CAD / month	5,692.25	441
CAD / week	1,450.00	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: 0% remote, 18% 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

Jobs in Burnaby, BC and nearby

Within 25 km

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Swim Recruiting

Machine Learning Scientist

Vancouver, BC, Canada
Greater Vancouver, BC, Canada

$100,000 to $150,000 CAD / year · Contract

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Job details

Pay: $100,000 to $150,000 CAD / year
Job type: Contract
Apply by: Dec 4, 2026
Experience: 3+ years of hands-on experience developing and researching deep learning models, with a strong emphasis on building architectures from scratch
Posting language: English
Posted: Nov 4, 2026

Original job description

A rare opportunity to do real, foundational deep learning research and see your models shipped into production at scale. If you're driven by hard problems, motivated by industrial-scale impact, and thrive when you can take ownership from whiteboard to deployment - this one is worth your attention.

Join a high-growth tech company at the forefront of industrial imaging, where your contributions directly shape how clients understand and manage assets at scale.
You won't be maintaining legacy pipelines or fine-tuning off-the-shelf models. This role is purpose-built for scientists who want to design and build deep learning architectures from scratch, tackling genuinely novel computer vision challenges across massive industrial datasets.
The team is actively expanding into new technologies with rapid growth forecasted. You're joining at an inflection point where you can shape direction, with the backing of an established, high-performing team.
Work alongside domain experts, data engineers, and platform teams who are deeply invested in making your models succeed in the real world. Small team culture means your contributions are visible, your ideas get heard, and your impact is never buried.

What & Why:

A fast-growing industrial technology company is looking for a mid-to-senior Machine Learning Scientist to join their growing team. The role is open due to team growth, with the organization scaling its model development capacity to support an expanding set of industrial applications that are moving toward large-scale deployment. This is a hands-on research position where you'll own the full arc of model development.

Who:

Our client is a Canadian-founded tech company that has built a proprietary platform disrupting how industrial operators assess the integrity of their critical infrastructure. They operate at the crossroads of advanced physics, machine learning, and engineering.

The position is fully-on site in the Greater Vancouver area.

You:

You will bring the following education, skills and experience to the role:

Master's or PhD degree in Computer Science, Electrical Engineering, or a related discipline
3+ years of hands-on experience developing and researching deep learning models, with a strong emphasis on building architectures from scratch
Deep proficiency in Python and modern deep learning frameworks - PyTorch is the primary stack but other skills likes JAX also considered
Demonstrated experience with vision tasks including object detection, instance segmentation, semantic segmentation, or anomaly detection
Excellent communication skills - you can translate complex model behaviour to non-ML audiences, gather context from domain experts, and rally collaborators around a research direction

Compensation:

$100,000 to $150,000 + competitive incentive program

Next Steps:

If the sound of this opportunity excites you, and you’re confident that it’s a good fit for your experience and career goals, then we’d love to hear from you! Please send your updated resume to us by applying to this posting and one of our awesome team of recruiters will be in touch.

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More about this job

Responsibilities

Research, design, and build deep learning architectures from scratch to address novel computer vision challenges in large industrial datasets. Own the full model development lifecycle, from research and experimentation through deployment at scale, collaborating with domain experts, data engineers, and platform teams.

Requirements

A master's or PhD in Computer Science, Electrical Engineering, or a related discipline, plus at least three years of hands-on deep learning model development and research experience. Requires strong Python and modern deep learning framework proficiency, experience with computer vision tasks, and the ability to communicate model behavior and collaborate with non-ML experts.

Skills

Deep Learning
Machine Learning Research
Computer Vision
Python
PyTorch
JAX
Object Detection
Instance Segmentation
Semantic Segmentation
Anomaly Detection
Model Deployment
Communication
Cross-Functional Collaboration

Visa sponsorship

Not detected in the job text

Keywords

Deep Learning
Machine Learning
Computer Vision
Python
PyTorch
JAX
Neural Network Architectures
Object Detection
Instance Segmentation
Semantic Segmentation
Anomaly Detection
Model Development
Model Deployment
Industrial Imaging
Industrial Infrastructure
Industrial Datasets
Research
Data Engineering
Platform Teams
Asset Integrity
Physics
Engineering
Large-Scale Deployment

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