Software development jobs in Canada

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

Counted Sep 26, 2026

Hiring at a glance

View jobs

Open jobs: 4,040
Employers: 1,488

Advertised starting pay

Average starting payCAD / year: $115,177Across 456 listings
Average starting payUSD / year: $139,934Across 117 listings
Average starting payCAD / hour: $54.97Across 67 listings

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

Where work happens

Remote: 10%407 listings
Hybrid: 40%1,634 listings
On-site: 49%1,961 listings

Not specified: 1% (38 listings)

Employers hiring include Amazon (117), Genetec (65), RBC (48).

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 2 months ago
Coherent Systems Architect - Mixed Signal AFE development
Nokia
Kanata, Ontario
Full-time
We are seeking a hands-on Coherent RF Architect to lead silicon bring-up, validation, and production test development for a mixed-signal Analog Front-End (AFE) featuring high-speed DACs,…
Added 2 months ago
Full Stack Developer (UI/UX Focus)
SuperQ Quantum Computing
Remote, Canada
Full-time · Remote
Added 2 months ago
Senior Full Stack Developer
BrainStation
Toronto, Ontario
$120,000 to $145,000 USD / year
Full-time
Added 2 months ago
Senior Software Engineer
Magical
Toronto, Ontario
Full-time
Added 2 months ago
Associate Software Engineer / Software Engineer
Applied Systems Canada
Toronto, Ontario
Full-time
…willing to try new things, and driven to deliver innovative software and services that make us indispensable to our customers – all within a culture built on values that make us…
Added 2 months ago
Associate Principal Software Engineer, Cloud & Edge Backend
Saviynt
Vancouver, British Columbia
$220,000 to $235,000 USD / year
Full-time
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Ingénieur(e) Principal(e) - Ingénierie RM&S
SOGECLAIR
Montreal, Quebec
Full-time
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Saviynt
Vancouver, British Columbia
$240,000 to $250,000 USD / year
Full-time
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Principal Software Engineer, Platform Engineering & Edge Infrastructure
Saviynt
Vancouver, British Columbia
$240,000 to $250,000 USD / year
Full-time
Added 2 months ago
Principal Software Engineer, Cloud & Edge Backend
Saviynt
Vancouver, British Columbia
$240,000 to $250,000 USD / year
Full-time
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Full Stack Developer
Kumaran Systems
Toronto, Ontario
Full-time
…technologies, along with a passion for building high-quality software…
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Edmonton, Alberta
Full-time
Catalis is a leading government Software as a Service (SaaS) and integrated payments provider, powering a wide range of government operations at the municipal, county, state, and federal…
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Software Developer I
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Full-time
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Toronto, ON
Full-time
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Toronto, ON
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Principal Software Engineer
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Richmond, BC
$40,000 CAD / year
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Vancouver, BC
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$240,000 to $285,000 USD / year
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Baseten

Software Engineer - GPU Networking & Distributed Systems

Montreal, QC, Canada

Pay: $165,000 to $330,000 USD / year
Job type: Full-time
Posting language: English
Posted: Jul 10, 2026

Apply About employer

Applications open in a new tab.

Original job description

About Baseten

Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products.

At Baseten, we are building the global operating system for distributed, heterogeneous AI hardware. We believe that as LLM and multi-modal workloads scale, the network is the computer. We are looking for foundational engineers to lead our GPU Networking efforts, making RDMA a first-class building block in our infrastructure and unlocking the next generation of distributed inference optimizations.

THE OPPORTUNITY

Networking and compute are no longer separate disciplines; they are converging. The massive throughput of H100, B200, and NVL72 architectures enables and demands a new approach where communication is co-optimized alongside computation. We are entering an era where the network is an active accelerator, leveraging smart hardware offloads and direct interconnects to ensure that data movement operates at wire-speed.

In this role, you will go beyond network configuration to architect the software fabric that unifies thousands of GPUs into a cohesive operating system. While you will leverage the best of the open-source ecosystem, you won't be limited by it. Where off-the-shelf solutions stop, you will build from scratch, engineering the primitives required to co-optimize communication and compute for Disaggregated Serving, Wide Expert Parallelism (WideEP), and lightening cold starts.

What You'll Do

Make RDMA First-Class: You will work on integrating RDMA/RoCE/InfiniBand capabilities directly into our inference stack, helping us move beyond TCP/IP to unlock order-of-magnitude improvements in bandwidth and latency.
Optimize Distributed Inference: You will implement and tune the networking layers necessary for efficient Disaggregated KV Cache Offload and WideEP, ensuring seamless communication across NVLink and InfiniBand for our MoE models.
Enable Serverless-Grade Startup Speeds for LLMs: You will work deeply with checkpointing and storage mechanisms to enable sub-10-second startup for trillion-parameter models.
Deep-Dive into Hardware: You will characterize and validate networking performance on bleeding-edge clusters (H100/H200, B200/B300, GB200/300 NVL72), writing the acceptance tests that ensure our hardware delivers peak achievable throughput and minimal latency.
Build Observability: You will design the tools that let us visualize packet flow, congestion, and effective bandwidth across the GPU interconnects, helping us diagnose complex distributed system behaviors.
Optimize Kernels: You will work with communication libraries (NCCL, NVSHMEM) and potentially write custom communication kernels to overlap compute and data transfer.

Who You Are

You have deep experience with high-performance networking protocols (InfiniBand, RoCE v2) and understand the physics of data movement.
You are fluent in C++ or Python, with the ability to bridge the gap between high-level logic and hardware. You have a deep understanding of the memory hierarchy in modern NVIDIA architectures (H100/Blackwell) and know how to optimize for it.
You like going deep. You aren't afraid to dive into TensorRT-LLM source code, write custom C++ / Python bindings, or debug NVLink topology issues.
You know when to use an off-the-shelf solution and when we need to build a custom solution because the upstream tools (like standard Kubernetes networking) are too slow for our needs.

HIGHLY PREFERRED:

Deep knowledge of NCCL, NVSHMEM, and UCX.
Experience with GPUDirect Storage (GDS) or high-performance filesystems like Weka or 3FS.
Familiarity with TensorRT-LLM, vLLM, or Sglang.
Experience running low-level benchmarks to "qualify" new hardware clusters.

Why join the Model Performance team?

Bleeding Edge Hardware: We are preparing to bring Blackwell (B200/B300) and then Rubin architectures online. You will be one of the first engineers in the industry optimizing networking for NVL72/GB300 racks.
We go deep: We operate at every depth. Whether it’s tuning hardware interconnects, writing custom communication kernels, or designing distributed inference strategies, we work across the entire stack to deliver performance that goes far and beyond.
High Impact: The networking optimizations you build will directly enable features that no one else in the industry has fully mastered yet, like seamless multi-node WideEP and instant model hydration.

Benefits

Competitive compensation, including meaningful equity.
100% coverage of medical, dental, and vision insurance for employee and dependents
Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
Paid parental leave
Fertility and family-building stipend through Carrot
Company-facilitated 401(k)
Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.

At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.

We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Compensation Range: $165K - $330K

Apply About employer

More about this job

Responsibilities

You will architect the software fabric that unifies thousands of GPUs into a cohesive operating system, integrating RDMA capabilities into the inference stack. Additionally, you will optimize distributed inference and enable serverless-grade startup speeds for large language models.

Requirements

Candidates should have deep experience with high-performance networking protocols and be fluent in C++ or Python. A strong understanding of modern NVIDIA architectures and the ability to optimize for them is also essential.

Skills

High-Performance Networking Protocols
C++
Python
Memory Hierarchy
TensorRT-LLM
NCCL
NVSHMEM
UCX
GPUDirect Storage
High-Performance Filesystems
Distributed Inference
Networking Layers
Data Movement
Custom Communication Kernels
Observability Tools
Acceptance Tests

Benefits

Competitive Compensation
Health Insurance
Flexible PTO
Paid Parental Leave
Fertility and Family-Building Stipend
401k

Visa sponsorship

Not detected in the job text

Keywords

Software Engineer
GPU Networking
Distributed Systems
AI
Inference
RDMA
RoCE
InfiniBand
TCP/IP
Disaggregated Serving
Wide Expert Parallelism
Checkpointing
Storage Mechanisms
Networking Performance
Bleeding-Edge Clusters
Packet Flow
Congestion
Effective Bandwidth
Communication Libraries
Custom Communication Kernels
NVIDIA
H100
B200
NVL72
TensorRT
Model Performance
Blackwell
Rubin Architectures
High Impact

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