Full-time jobs in Canada

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

221,906 listings · 38,601 employers Counted Oct 12, 2026. How we count

About these jobs

Employers hiring include Walmart Canada (4,882 listings), Loblaw Companies Limited (2,026 listings), Walmart (1,591 listings).

Common roles: Cook, Project manager, Sales representative.

48,460 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	31,838
CAD / year	80,000.00	13,888
USD / year	100,000.00	1,047
USD / hour	20.00	413
CAD / month	4,867.00	279
CAD / week	1,445.00	33
CAD / day	400.00	24
GBP / year	40,000.00	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: 2% remote, 16% hybrid, 82% on-site, 1% 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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Added 6 hours ago
MG
Coordinator, Mental Health Services
Michael Garron Hospital
Toronto, ON
- Full-time
Added 6 hours ago
NG
financial clerk - financial sector
NSUS Group
Toronto, ON · North York, ON
- Full-time
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UF
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United for Literacy formerly Frontier College
Toronto, ON
- $25 CAD / hour
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LC
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Loblaw Companies Limited
Vaughan, ON
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LC
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Hamilton, ON
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Brantford, ON
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LC
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Loblaw Companies Limited
Montreal, QC
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NF
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No Frills
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Loblaw Companies Limited
Calgary, AB
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BF
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TH
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LC
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Vancouver, BC
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Mississauga, ON · Ajax, ON
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No Frills
Quinte West, ON
- Full-time
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Grocery Department Manager Full Time Evening
No Frills
Cobourg, ON
- Full-time
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Produce Department Manager Full Time Day
No Frills
Brighton, ON
- Full-time
Added 6 hours ago
D
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Vancouver, BC
- $19.67 to $28.54 CAD / hour
- Full-time
Added 6 hours ago
FS
Grocery Department Manager Full Time Night
Fortinos Supermarket Ltd
Oakville, ON
- Full-time
Added 6 hours ago
NF
Bakery InStore Department Manager Full Time Day
No Frills
Tottenham, ON
- Full-time
Added 6 hours ago
FS
Perpetual Inventory Department Manager Full Time Day
Fortinos Supermarket Ltd
Oakville, ON
- Full-time
Added 6 hours ago
FS
Bakery InStore Department Manager Full Time Day
Fortinos Supermarket Ltd
Brampton, ON
- Full-time

Ericsson

Baseband System Developer Co-op

Ottawa, ON, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Nov 7, 2026
Working hours: 40 hours per week
Posting language: English
Posted: Oct 8, 2026

Original job description

Grow with us

Baseband System Developer Co-op

Location: Ottawa, ON.

Duration: 8 – 16 months (for co-ops)

Start date: January 11th, 2027

Please upload your unofficial transcript when applying. (Use the "Cover letter" uploading tab.) Please indicate in your resume or a cover letter how many months you are available for.

At this time, Ericsson Canada Inc. does not provide immigration assistance/sponsorship now or in the future for this position.

About this opportunity:

As the tech firm that was instrumental in creating the mobile world, and with more than 54,000 patents to our name, we’ve made it our business to make a mark. When joining our team at Ericsson you are empowered to learn, lead, and perform at your best, shaping the future of technology. This is a place where you're welcomed as your own perfectly unique self, and celebrated for the skills, talent, and perspective you bring to the team. Come and be where it begins!

What you will do:

Apply supervised and/or reinforcement learning algorithms to address complex challenges in 5G Wireless Physical Layer and Radio Resource Management
Collaborate with subject matter experts to improve the performance of AI-integrated system-level wireless simulators
Research new software development tools and technologies, and support implementation in alignment with industry best practices
Contribute to innovation initiatives, including Ericsson Invention Disclosures and Patents

The skills you bring:

Knowledge of wireless communications and machine learning
Experience with ML techniques such as reinforcement learning, federated learning, deep learning, GAN, DQN, LSTM, SVM, or random forest
Understanding of Transformer architecture, its variants, and practical applications
Familiarity with Large Language Models (LLMs)
Experience with ML frameworks such as TensorFlow, PyTorch, or Keras
Experience in data preprocessing, cleaning, and feature engineering
Experience with system-level cellular communication simulators
Basic understanding of LTE and NR 3GPP specifications (Physical Layer, Radio Resource Management, Mobility)
Strong analytical, problem-solving, and communication skills
Ability to work effectively both collaboratively and independently

Eligibility requirements:

2.7+ GPA on a 4.0 scale or equivalent
Uploading an unofficial copy of your transcript
Actively enrolled in an accredited undergraduate, master’s, or PhD on a full-time basis at a four-year college or university at the time of the co-op
Be available to work 40 hours per week

What happens once you apply?

Click Here to find all you need to know about what our typical hiring process looks like.

Ericsson uses a merit-based hiring approach that values people with different experiences, perspectives and skillsets. We truly believe this approach drives innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity employer, learn more.

If you need assistance or to request an accommodation due to a disability, please contact Ericsson at hr.direct.americas@ericsson.com.

DISCLAIMER: The above statements are intended to describe the general nature and level of work being performed by employees in this position. They are not an exhaustive list of all responsibilities, duties and skills required for this position, and you may be required to perform additional job tasks as assigned.

Primary country and city: Canada (CA) || Ottawa (Country/ City)

Job details: Developer

Compensation And Benefits At Ericsson

At Ericsson, we know that our people are the key to our success. We offer a competitive package to help with your individual needs and goals.

Your Pay

The salary offered is dependent on various factors including, but not limited to, location, and the candidate’s combination of job-related knowledge, qualifications, skills, education, training, and experience.

The salary range for this position is:

Bachelors: $25.5/hr CAD - $34.5/hr CAD

Masters: $37/hr CAD

PhD: $41/hr CAD

Apply About employer

More about this job

Responsibilities

Apply supervised and reinforcement learning methods to challenges in 5G wireless physical-layer systems and radio resource management, and collaborate with experts to improve AI-integrated wireless simulators. Research and implement software tools using industry best practices, and contribute to innovation initiatives such as invention disclosures and patents.

Requirements

Applicants must be full-time students enrolled in an accredited undergraduate, master's, or PhD program, have a GPA of at least 2.7 on a 4.0 scale, submit an unofficial transcript, and be available to work 40 hours per week. Relevant knowledge includes wireless communications, machine learning methods and frameworks, transformers and LLMs, data preparation, cellular simulators, and LTE/NR specifications; strong analytical, problem-solving, and communication skills are also required.

Skills

Wireless Communications
Machine Learning
Reinforcement Learning
Federated Learning
Deep Learning
Transformer Architecture
Large Language Models
TensorFlow
PyTorch
Keras
Data Preprocessing
Feature Engineering
LTE and NR 3GPP Specifications
Physical Layer
Radio Resource Management

Visa sponsorship

Not detected in the job text

Keywords

5G
Wireless Communications
Physical Layer
Radio Resource Management
Supervised Learning
Reinforcement Learning
Federated Learning
Deep Learning
Generative Adversarial Networks
Deep Q-Networks
LSTM
Support Vector Machines
Random Forest
Transformer Architecture
Large Language Models
TensorFlow
PyTorch
Keras
Data Preprocessing
Data Cleaning
Feature Engineering
LTE
NR
3GPP Specifications
Software Development Tools
Wireless System Simulation
Invention Disclosures
Patents

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