Jobs in Coquitlam, BC and nearby

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

33,768 listings · 6,411 employers Counted Oct 28, 2026. How we count

About these jobs

Employers hiring include Vancouver Coastal Health (871 listings), Fraser Health (772 listings), Health Match BC (684 listings).

Common roles: Registered nurse, Retail sales associate, Software engineer.

8,658 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	33.00	5,227
CAD / year	82,450.00	2,588
CAD / month	5,692.25	360
USD / hour	18.75	199
USD / year	90,000.00	111

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, 19% hybrid, 81% 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 Coquitlam, BC and nearby

Within 25 km

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Added 1 day ago
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Coquitlam, BC
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MetaOptima Technology Inc.

Machine Learning Engineer

Vancouver, BC, Canada

$100,000 to $140,000 CAD / year · Full-time

Apply About employer

Applications open in a new tab.

Job details

Pay: $100,000 to $140,000 CAD / year
Job type: Full-time
Apply by: Apr 25, 2027
Posting language: English
Posted: Oct 2, 2026

Original job description

Location: Vancouver, BC - Downtown

About MetaOptima:

Join MetaOptima to make a difference in the lives of millions as we revolutionize the dermatology industry with software, hardware and AI for faster, more effective, and affordable care. MetaOptima is full of passionate, innovative people who thrive on working together as a team to build smart, life-saving technologies for medical professionals and their patients. Our casual, open-office culture welcomes fresh ideas from the minds of doers. Join us to add your voice to our vision while working with a cool group of people set on making their mark on the world. We take pride in what we’ve accomplished together, and can’t wait to see how you’ll help us grow.

Job Summary:

As a Machine Learning Engineer, you will join a small, high-impact R&D team and own the full ML lifecycle - from research and rapid prototyping through data pipelines, model training, and cloud deployment. Your work will directly shape clinical-grade computer vision systems that help dermatologists and their patients around the world.

Responsibilities

Take vision problems from business needs through prototype to production system: data acquisition, training, evaluation, and deployment on AWS or GCP.
Rapidly prototype research ideas and estimate the effort required to develop an MVP.
Develop tooling to clean, label, and manage medical image datasets.
Analyze MVP performance to determine how to scale solutions for full cloud deployment on AWS or GCP.
Optimize models for inference and keep them running reliably once deployed.
Present findings clearly to both technical and non-technical stakeholders.

Qualifications (must‑have)

Master's or PhD in Computer Science or a related quantitative field, plus 2+ years of full-time industry experience building production-grade computer vision and machine learning systems.
Strong software engineering fundamentals: version control, testing, and code review, with the discipline to maintain several models and services at once rather than one project at a time.
Demonstrated end-to-end ownership of ML systems in production: data extraction and exploratory analysis, modeling and training, evaluation, drift detection, and serving.
Strong proficiency in Python, PyTorch, and ML/scientific computing libraries (scikit-learn, scipy, numpy), including optimizing models for inference with ONNX, TensorRT, or quantization.
Breadth across computer vision, not just deep learning (feature detection and matching, camera geometry and calibration, and registration) and the judgment to know when a classical method beats a learned one.
Owned ML services running in production on AWS or GCP, containerized with Docker, orchestrated on Kubernetes, and shipped through CI/CD.
Experience designing ML approaches, choosing the right metrics to evaluate them, and iterating toward a solution that moves a clinical or business outcome rather than a benchmark.
Self-starter with strong communication, documentation, and presentation skills.
Able to work effectively in a fast-paced startup environment.

Preferred Qualifications:

Experience with 3D vision and/or multiview geometry.
Experience in clinical or regulated environments

Why Join Us

You’ll play a pivotal role in advancing next-generation imaging technology for dermatology, helping transform how skin is captured, reconstructed, and analyzed worldwide.

If you’re excited to turn cutting-edge machine learning research into clinical-grade imaging technology, we’d love to hear from you.

Apply About employer

More about this job

Responsibilities

Own the full machine learning lifecycle for clinical-grade computer vision systems, from research, data preparation, and prototyping through model training, evaluation, and cloud deployment. Optimize and maintain production models, develop medical-image dataset tooling, and communicate findings to technical and non-technical stakeholders.

Requirements

Requires a master's or PhD in computer science or a related quantitative field and at least two years of industry experience building production-grade computer vision and machine learning systems. Candidates must have strong Python and PyTorch skills, end-to-end production ML ownership, cloud and container orchestration experience, and broad computer vision expertise; 3D vision and regulated-environment experience are preferred.

Skills

Python
PyTorch
Computer Vision
Machine Learning
Medical Image Processing
Model Training
Model Evaluation
Inference Optimization
ONNX
TensorRT
AWS
Google Cloud Platform
Docker
Kubernetes
CI/CD
3D Vision

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Computer Vision
Clinical-Grade Systems
Medical Imaging
Dermatology
Python
PyTorch
Scikit-Learn
SciPy
NumPy
ONNX
TensorRT
Quantization
AWS
Google Cloud Platform
Docker
Kubernetes
CI/CD
Data Pipelines
Model Training
Model Evaluation
Drift Detection
Model Serving
Feature Detection and Matching
Camera Geometry
Camera Calibration
Image Registration
3D Vision
Multiview Geometry
Regulated Environments

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