Full-time jobs in Canada

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

192,316 listings · 19,903 employers Counted Oct 6, 2026. How we count

About these jobs

Employers hiring include Walmart Canada (4,968 listings), Starbucks Coffee Company (1,899 listings), WSP in Canada (1,543 listings).

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

21,513 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 / year	81,702.24	12,468
CAD / hour	24.00	6,331
USD / year	95,500.00	1,061
USD / hour	20.00	424
CAD / month	5,538.94	235
CAD / week	1,400.00	32
GBP / hour	35.00	15
USD / month	5,000.00	15
CAD / day	380.00	14
GBP / year	40,000.00	12

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, 18% hybrid, 80% 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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Added 4 hours ago
Senior Engineer - Mechanical Systems and Equipment
Westinghouse Electric Company, LLC
Kitchener, ON
Added 4 hours ago
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Senior Manager, Technology Risk Management
BMO
Toronto, ON · FCP
- Full-time
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Senior Project Controls Specialist, Planning & Scheduling
Stantec
Burnaby, BC
- Full-time
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Supply Chain Coordinator (Project Procurement)
BWXT
Cambridge, ON
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Administrative Assistant
I R C M
Montreal, QC
- Full-time
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Montreal, QC
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Montreal, QC
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Montreal, QC · Mirabel, QC
- Full-time
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AB · Lloydminster, AB
- Full-time
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Edmonton, AB
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Nova Scotia Health and IWK Health
Sheet Harbour 36, NS
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Nova Scotia Health and IWK Health
Halifax, NS
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Toronto, ON · Waterloo, ON
- Full-time
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Sr. Mechanical Engineer / Project Manager - Buildings
SearchLabs
Markham, ON
- Full-time
Added 4 hours ago
A
Spécialiste en analyse des contraintes - Structures métalliques / Stress Analysis Specialist - Metallic Structures
Airbus
Montreal, QC
- Full-time
Added 4 hours ago
GB
power brake operator - metal fabrication
Groupe Bibeau Inc.
Saint-Felix-de-Valois, QC
- Full-time
Added 4 hours ago
I-
BIM Coordinator – Piping / Building Mechanical Systems (Industrial Refrigeration, Plumbing, Heating & Cooling)
I8IS - Infiniti Software Solutions
Quebec, QC
- Full-time

Google DeepMind

Research Developer, Frontier AI Incubation, DeepMind

Montreal, QC, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Nov 5, 2026
Posting language: English
Posted: Oct 6, 2026

Original job description

This posting is for an existing vacancy.

Google utilizes AI tools to assist in assessing candidates in our hiring processes.

Minimum qualifications:

Bachelor's degree in Computer Science, Machine Learning, Mathematics, Statistics, or equivalent practical experience.
2 years of experience in machine learning, algorithm design, data structures, or distributed software systems.
2 years of experience programming in Python or C++.
1 year of experience taking technical projects or machine learning systems from conceptual formulation to implementation and deployment.

Preferred qualifications:

Experience developing, fine-tuning, or optimizing foundation models including techniques such as reinforcement learning from human/AI feedback, supervised fine-tuning, parameter-efficient tuning, or inference optimization.
Experience or interest in personalization, adaptive systems, user modeling, retrieval-augmented generation, or agentic memory architectures.
Experience with machine learning frameworks and large-scale model training or serving infrastructure.
Experience collaborating across research and product boundaries to co-design technical architectures.
Experience in scientific analysis, technical problem-solving, and technical communication.

About The Job

At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.

Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

Canada: $185000 - $190000 (CAD) + 15% bonus target + equity + benefits

Responsibilities

Learn more about benefits at Google .

Design, train, and optimize foundational algorithms and ML systems (e.g., personalized model adaptation, agentic workflows, contextual memory architectures, dynamic prompt optimization, and multimodal reasoning).
Lead end-to-end technical development from algorithmic design and experimental prototyping to production-grade architecture and scaled serving infrastructure.
Partner directly with Google development and product teams to integrate and harden our core technologies within production environments (e.g., Project Helix, agent workspaces, and intelligent system integrations).
Formulate novel automated and human-in-the-loop evaluation methodologies to measure capability gains, latency/compute efficiency, alignment, and personalization fidelity.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .

Apply About employer

More about this job

Responsibilities

Design, train, and optimize foundational algorithms and machine learning systems, taking projects from experimental prototypes through production architecture and scaled serving. Collaborate with product and development teams to integrate technologies, and create evaluation methods to measure capability, efficiency, alignment, and personalization.

Requirements

A bachelor's degree in computer science, machine learning, mathematics, statistics, or equivalent practical experience is required, along with at least two years of relevant technical experience and two years programming in Python or C++. Candidates also need one year taking technical projects or machine learning systems from concept through implementation and deployment; experience with foundation models, personalization, large-scale infrastructure, and research-product collaboration is preferred.

Skills

Machine Learning
Algorithm Design
Python
C++
Foundation Models
Reinforcement Learning From Human or AI Feedback
Supervised Fine-Tuning
Parameter-Efficient Tuning
Inference Optimization
Personalization
Retrieval-Augmented Generation
Agentic Memory Architectures
Large-Scale Model Training
Model Serving Infrastructure
Evaluation Methodologies
Multimodal Reasoning

Benefits

Bonus
Equity
Benefits

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Algorithm Design
Data Structures
Distributed Software Systems
Python
C++
Foundation Models
Reinforcement Learning From Human or AI Feedback
Supervised Fine-Tuning
Parameter-Efficient Tuning
Inference Optimization
Personalization
Adaptive Systems
User Modeling
Retrieval-Augmented Generation
Agentic Memory Architectures
Large-Scale Model Training
Model Serving Infrastructure
Technical Architecture
Scientific Analysis
Experimental Prototyping
Production Deployment
Human-in-the-Loop Evaluation
Latency Optimization
Compute Efficiency
Alignment
Multimodal Reasoning
Dynamic Prompt Optimization
Agentic Workflows

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