Software development jobs in Canada

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

Counted Oct 9, 2026

Hiring at a glance

View jobs

Open jobs: 4,013
Employers: 1,505

Advertised starting pay

Average starting payCAD / year: $114,760Across 455 listings
Average starting payUSD / year: $143,283Across 104 listings
Average starting payCAD / hour: $50.54Across 82 listings
Average starting payUSD / hour: $67.66Across 10 listings

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

Where work happens

Remote: 10%390 listings
Hybrid: 41%1,663 listings
On-site: 48%1,932 listings

Not specified: 1% (28 listings)

Employers hiring include Amazon (114), Genetec (62), Electronic Arts (51).

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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Added 7 mins ago
VC
Software developer
Vaisesika Consulting Inc.
Toronto, ON
- From $62.5 CAD / hour
- Full-time
- On-site
Added 23 mins ago
KR
Fresh Graduate – Java Full Stack Developer
KTek Resourcing
Toronto, ON
- $60,000 to $70,000 CAD / year
- Full-time
We have an exciting opportunity for a Java Full Stack Developer for recent graduates who are passionate about software development and looking to start their careers in enterprise…
Added 1 hour ago
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- Full-time
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Toronto, ON
- Full-time
Added 2 hours ago
T
Staff Software Engineer, ML Infra & Distributed Systems
Tubi
Toronto, ON
- Full-time
As a Staff Software Engineer on the ML Infrastructure team, you will collaborate closely with the Machine Learning and Product teams to build world-class machine learning inference…
Added 3 hours ago
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- Full-time
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As a Software Development Engineer, you'll design massively scalable distributed systems hand
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- Full-time
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Toronto, ON
- Part-time
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Vancouver, BC
- Full-time
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Richmond Hill, ON
- From $56.49 CAD / hour
- Full-time
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Added 7 hours ago
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Richmond Hill, ON
- From $48.08 CAD / hour
- Full-time
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Application Programmer
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Canada
- Contract
Added 7 hours ago
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G Square Builders Ltd.
Rocky View, AB
- From $41 CAD / hour
- Full-time
- On-site
Added 8 hours ago
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Software Developer Embedded Systems I (Full Time) - Canada
Cisco
AB · Vancouver, BC · Ottawa, ON · Montreal, QC · Kanata, Ontario · Calgary, Alberta · Saint-Laurent, Quebec
- Full-time
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- From $36.92 CAD / hour
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Saskatoon, SK
- From $37.55 CAD / hour
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Added 9 hours ago
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- $38.46 to $45 CAD / hour
- Full-time
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- Full-time
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Added 9 hours ago
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- Full-time

Tubi

Staff Software Engineer, ML Infra & Distributed Systems

Toronto, ON, Canada

$164,600 - $235,100 CAD · Full-time

Apply About employer

Applications open in a new tab.

Job details

Pay: $164,600 - $235,100 CAD
Job type: Full-time
Apply by: Feb 5, 2027
Posting language: English
Posted: Oct 5, 2026

Original job description

About The Role:

As a Staff Software Engineer on the ML Infrastructure team, you will collaborate closely with the Machine Learning and Product teams to build world-class machine learning inference platforms. These platforms power essential services like personalized recommendations, search, and content understanding across Tubi.

A core responsibility of this team is developing and maintaining low-latency ML model serving systems that support Deep Learning, LLM, and Search models. This involves building self-service infrastructure and critical components such as the inference engine, feature store, vector store, and experimentation engine.

You will improve the way we deploy and operate our services and even contribute to open-source projects. This role grants the architectural freedom to explore new frameworks, lead critical cross-functional projects, and transform the capabilities of our ML and Product teams.

Responsibilities:

Design and build scalable, high throughput, and low latency distributed systems using Scala
Build reusable components and services that serve various ML applications like Personalization, Search, Ads and Exploration
Partner closely with ML engineers to understand their challenges and limitations and develop scalable solutions to address them. Proactively recommend solutions to keep our ML Inference stack state of the art.
Take a data driven approach to identifying & optimizing latency, cost, and efficiency of our infra. Lead large scale cross functional refactorings if necessary
Mentor other engineers on the team on system design, effective incident management, interviewing, leveraging LLMs for work, etc.
Collaborate with ML, Product, and cross functional engineering teams to define the long term vision and architecture for ML Infrastructure at Tubi.

Your Background:

Experience designing and building scalable, distributed systems in any modern backend language (e.g., Scala, Java, Python, Go, C++); experience with Scala or JVM based language is a plus.
Strong experience with AWS or an equivalent cloud platform
Experience building online microservices at scale with low latency serving
Experience with both SQL (e.g. Postgres) and NoSQL databases (e.g. Cassandra), message brokers (e.g. Kafka), and caches (e.g. Redis)
Experience with containerization technologies, such as Docker or Kubernetes
Led the response and resolution efforts for multiple major, large-scale incidents

Bonus:

Familiarity with the machine learning infrastructure like inference engines (e.g. torschserve, triton, vLLM), vector stores (e.g. LanceDB, FAISS), feature stores (e.g. Feast), ElastiCache, model training orchestration, etc.
Understanding of ML model training pipelines and model internals. Experience with Recommender Systems, Search, Autocomplete and Ads ML is a plus
Previous experience with Akka, Erlang, Elixir or Go
Proficient in data-driven analysis of complex A/B testing results

About Tubi:

Tubi is a free streaming service that entertains over 100 million monthly active users. Tubi offers the world's largest collection of Hollywood movies and TV shows, thousands of creator-led stories and hundreds of Tubi Originals made for the most passionate fans. Headquartered in San Francisco and founded in 2014, Tubi is part of Tubi Media Group, a division of Fox Corporation.

Pursuant to local pay disclosure requirements, the pay range for this role, with final offer amount dependent on education, skills, experience, and location is as listed annually below.

This role is also eligible for an annual discretionary bonus, long-term incentive plan, and various benefits including medical/dental/vision, insurance, vacation/paid time off and other benefits in accordance with applicable plan documents.

Toronto, Canada

$164,600 - $235,100 CAD

Tubi Media Group Is a Division Of Fox Corporation, And The FOX Employee Benefits Summarized Here, Covers The Majority Of Employee Benefits. The Following Distinctions Below Outline The Differences Between The Tubi And FOX Benefits:

For all salaried employees, in lieu of the FOX Vacation policy, Tubi offers a Flexible Time Off Policy to manage all personal matters.

For all full-time, regular employees, in lieu of FOX Paid Parental Leave, Tubi offers a generous Parental Leave Program, which allows parents twelve (12) weeks of paid bonding leave (top up in Canada) within the first year of birth, adoption, surrogacy, or foster placement of a child in addition to applicable government leave program(s) and FOX’s short-term disability policy (if applicable). This time is 100% paid through a combination of any applicable government leaves and wage-replacement programs in addition to contributions made by Tubi.

For all full-time, regular employees, Tubi offers a monthly wellness reimbursement.

About Tubi:

Boldly built for every fandom, Tubi is a free streaming service that entertains over 100 million monthly active users. Tubi offers the world's largest collection of Hollywood movies and TV shows, thousands of creator-led stories and hundreds of Tubi Originals made for the most passionate fans. Headquartered in San Francisco and founded in 2014, Tubi is part of Tubi Media Group, a division of Fox Corporation.

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, gender identity, disability, protected veteran status, or any other characteristic protected by law. We will consider for employment qualified applicants with criminal histories consistent with applicable law.

Apply About employer

More about this job

Responsibilities

Design and build scalable, high-throughput, low-latency distributed systems and reusable infrastructure for machine learning applications, including inference, feature, and vector stores. Partner with ML, Product, and engineering teams to shape architecture, optimize latency and cost, lead cross-functional initiatives, and mentor engineers.

Requirements

Candidates should have experience building scalable distributed systems and low-latency online services, along with cloud platforms, SQL and NoSQL databases, message brokers, caches, and containerization technologies. The role also calls for leading major incident responses; Scala/JVM experience and familiarity with ML infrastructure, model pipelines, recommendation or search systems, and A/B testing are advantageous.

Skills

Distributed Systems
Scala
Machine Learning Infrastructure
Low-Latency Serving
Microservices
AWS
SQL
NoSQL
Kafka
Redis
Docker
Kubernetes
Incident Management
System Design
A/B Testing
Mentoring

Benefits

Annual Discretionary Bonus
Long-Term Incentive Plan
Medical Insurance
Dental Insurance
Vision Insurance
Flexible Time Off
Paid Parental Leave
Wellness Reimbursement

Visa sponsorship

Not detected in the job text

Keywords

Scala
Java
Python
Go
C++
AWS
Distributed Systems
Machine Learning Infrastructure
Inference Engines
Model Serving
Feature Stores
Vector Stores
Deep Learning
Large Language Models
Search
Personalization
Recommendation Systems
Microservices
PostgreSQL
Cassandra
Kafka
Redis
Docker
Kubernetes
Akka
Erlang
Elixir
Model Training Pipelines
A/B Testing
Incident Management

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