Software development jobs in Canada

Explore software development jobs in Canada. Choose a role or place to find work that fits.

Counted Sep 22, 2026

Hiring at a glance

View jobs

Open jobs: 4,156
Employers: 1,543

Advertised starting pay

Average starting payCAD / year: $116,364Across 455 listings
Average starting payUSD / year: $140,203Across 120 listings
Average starting payCAD / hour: $55.84Across 75 listings

Employer-advertised starting pay, not employee salaries. Currencies and pay periods stay separate.

Where work happens

Remote: 10%411 listings
Hybrid: 40%1,682 listings
On-site: 49%2,022 listings

Not specified: 1% (41 listings)

Employers hiring include Amazon (115), Genetec (64), RBC (59).

Sources & calculation notes

These figures describe the listings on this role page at the date shown, not the whole job market. Listings can change.

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.

Hybrid and on-site classifications may be inferred from descriptions. Check the original ad. How we count

Software development jobs in Canada

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Software Engineer II, Machine Learning - Slack
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Salesforce

Software Engineer II, Machine Learning - Slack

Toronto, ON, Canada

Pay: For Ontario-based roles, the base salary hiring range for this position is CAD 130,300 to CAD 179,200 annually.
Job type: Full-time
Apply by: Oct 8, 2026
Posting language: English
Posted: Sep 8, 2026

Apply About employer

Applications open in a new tab.

Original job description

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

Job Category

Software Engineering

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword - it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

Job Description Summary

Slack is looking for a Machine Learning Engineer to craft and implement features, services, API methods, and models to leverage our data to make Slack a fabulous, robust, safe, and valuable product for our users. We work on applications across search, agentic systems, recommendation, and security, but ultimately are looking for engineers who can help drive impact with machine learning across the organization.

At Slack, That Impact Can Be Huge

We have over 10 million daily active users relying on our product.
At peak usage, a million messages a minute pass through Slack.
During the week, our users spend over a billion minutes a day active in our product.

Machine learning engineers at Slack touch a great variety of parts of our technical stack. At different points, you might find yourself building data pipelines, training recommendation models, fine tuning LLMs, implementing features in our application, or analyzing experiment data. We don’t expect everyone to be an expert in everything, but we are looking for candidates with experience in Machine Learning, a strength in at least a couple of these, and who are excited to learn the rest.

This is a practical machine learning team, not a research team. Our goal is to deliver business value with machine learning and data in whatever form that takes. Sometimes that means bootstrapping something simple like a logistic regression and moving on. Other times that means developing sophisticated, finely tuned models and novel solutions to Slack’s unique problem space. We are looking for engineers who are driven by driving impact for our business, building great products for our customers, and delivering robust, reliable services with machine learning.

What You Will Be Doing

Develop ML models supporting ranking, retrieval, and generative AI use-cases.
Brainstorm with Product Managers, Designers and Frontend Engineers to conceptualize and build new features for our large (and growing!) user base.
Produce high-quality results by leading or contributing heavily to large multi-functional projects that have a significant impact on the business.
Actively own features or systems and define their long-term health, while also improving the health of surrounding systems.
Support in the development of sustainable data collection pipelines and management of ML features.
Assist our skilled support team and operations team in triaging and resolving production issues.
Mentor other engineers and deeply review code.
Improve engineering standards, tooling, and processes.

You may be a fit for this role if you have:

Experience with functional or imperative programming languages: PHP, Python, Ruby, Go, C, Scala or Java.
Built with common ML frameworks like pytorch, Tensorflow, Keras, XGBoost, or Scikit-learn
Experience building batch data processing pipelines with tools like Apache Spark, Hadoop, EMR, Map Reduce, Airflow, Dagster, or Luigi.
Fine tuned LLMs or BERT models.
An analytical and data driven mindset, and know how to measure success with complicated ML/AI products.
Put machine learning models or other data-derived artifacts into production at scale.
Led technical architecture discussions and helped drive technical decisions within the team.
The ability to write understandable, testable code with an eye towards maintainability.
Strong communication skills and you are capable of explaining complex technical concepts to designers, support, and other specialists.
Strong computer science fundamentals: data structures, algorithms, programming languages, distributed systems, and information retrieval.
A bachelor's degree in Computer Science, Engineering, Statistics, Mathematics or a related field, or you have equivalent training, fellowship, or work experience.

Bonus Points

Expertise in conversational agentic systems.
Expertise in retrieval systems and search algorithms.
Familiarity with vector databases and embeddings.
Knowledge of using multiple data types in RAG solutions including structured, unstructured, and knowledge graphs.
Broad experience across NLP, ML, and Generative AI capabilities.

Unleash Your Potential

When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future - but to redefine what’s possible - for yourself, for AI, and the world.

Accommodations

If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form.

Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates’ resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.

Posting Statement

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions.

For Ontario-based roles, the base salary hiring range for this position is CAD 130,300 to CAD 179,200 annually.

The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.

This posting is to fill a vacancy on our team, unless otherwise noted.

Apply About employer

More about this job

Responsibilities

Develop and implement ML models for ranking, retrieval, and generative AI to enhance Slack's product features. Collaborate with cross-functional teams to build scalable data pipelines and maintain high-quality production services.

Requirements

Requires a bachelor's degree in Computer Science or a related field and proficiency in ML frameworks and programming languages. Candidates must have experience deploying ML models at scale and building batch data processing pipelines.

Skills

Machine Learning
Python
PyTorch
TensorFlow
Apache Spark
LLM Fine-tuning
Generative AI
Data Pipelines
Distributed Systems
Information Retrieval
PHP
Ruby
Go
Java
Scala
Scikit-learn

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Generative AI
LLM
BERT
RAG
Vector Databases
Embeddings
NLP
Apache Spark
Hadoop
Airflow
Dagster
Luigi
PyTorch
TensorFlow
Keras
XGBoost
Scikit-learn
Python
Java
Go
Scala
PHP
Ruby
Distributed Systems
Information Retrieval
Agentforce
AI CRM
Data Pipelines
Ranking

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