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Added 57 mins ago
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Technical Sales Intern- Mississauga
Captiveaire - Region 114 Western PA
Mississauga, ON
- Volunteer
…December 2026 or May 2027 and has an interest in being a Sales Engineer. The role will be part time in the…
Added 1 hour ago
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Process Engineer, Production
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- $85,000 to $95,000 CAD / year
- Full-time
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- $70,000 to $90,000 CAD / year
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Added 1 hour ago
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Toronto, ON
- Full-time
A valid Aircraft Maintenance Engineer (AME) license is required.
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- Full-time
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Join the team as Twilio’s next Staff Software Engineer.
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Hold a valid Aircraft Maintenance Engineer License (HKCAR-66 or equivalent EASA/FAA certification).
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Sr. Software Development Engineer, AI Models
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Analog/Mixed-Signal SerDes Design Engineer
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AMD is seeking a Software Engineer, AI & Engineering Productivity Tools to build platforms, automation, and AI-powered tools that improve engineering productivity across ASIC design and…
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Added 2 hours ago
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Senior Embedded Software Designer
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electronics research engineer
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Added 2 hours ago
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Professional Services Consultant
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Permanent North American Gaeltacht, ON
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…The role is suited to an experienced Windows infrastructure engineer with practical capability across Azure, Microsoft 365, identity, networking and…

Microsoft

Principal Software Engineer

Vancouver, BC, Canada

Full-time

Apply About employer

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Job details

Job type: Full-time
Posting language: English
Posted: Oct 2, 2026

Original job description

Overview

Do you want to help shape the future of AI infrastructure and influence the hardware-software co-design decisions powering Microsoft's next generation of AI platforms?

Join the Systems Planning and Architecture (SPARC) team within Azure Hardware Systems and Infrastructure (AHSI), where we are building infrastructure for some of the world's most demanding AI workloads. Our team drives model enablement, performance optimization, and hardware-software co-design across Microsoft's custom AI accelerators and cloud-scale AI systems.

As a Principal Software Engineer, you will provide technical leadership for enabling and optimizing frontier-scale AI models on Microsoft AI accelerators. You will work across hardware architecture, compilers, kernels, frameworks, runtimes, and model teams to define performance strategies, influence future platform investments, and improve training and inference efficiency at scale. This opportunity places you at the intersection of AI systems, distributed computing, and accelerator architecture, with the ability to influence technical direction across multiple engineering organizations.

This role is flexible and offers a hybrid work model with three days per week in the office.

Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees, we come together with a growth mindset, innovate to empower others, and collaborate to achieve our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Responsibilities

Lead technical strategy for enabling and optimizing frontier-scale AI models across Microsoft AI accelerators and cloud-scale AI infrastructure.
Architect and optimize AI systems across hardware, compilers, kernels, frameworks, runtimes, and distributed infrastructure to improve training and inference performance.
Partner with hardware architecture teams on hardware-software co-design, influencing accelerator features, memory systems, interconnects, execution models, and future silicon roadmaps.
Drive performance optimization across kernels, communication, memory movement, quantization, attention, mixture-of-experts (MoE), and other critical AI workloads.
Architect distributed training and inference solutions spanning large accelerator clusters, including parallelism, communication, memory management, and scaling strategies.
Drive model enablement and performance improvements across AI frameworks and inference technologies such as PyTorch, Triton, vLLM, SGLang, and related ecosystems.
Lead architecture reviews and complex cross-organization technical initiatives, build alignment across engineering teams, mentor engineers, and provide technical recommendations that inform Microsoft's long-term AI infrastructure strategy.

Qualifications

Required/minimum qualifications

Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Experience partnering with hardware architecture teams on hardware-software co-design, accelerator enablement, or performance optimization.

Other Requirements

Ability to meet Microsoft, customer, and/or government security screening requirements, including Microsoft Cloud Background Check requirements.

Preferred Qualifications

7+ years of experience developing and optimizing high-performance AI systems, kernels, or accelerator software using CUDA, ROCm, Triton, or similar programming models.
Deep experience optimizing large-scale AI workloads, including attention, mixture-of-experts (MoE), quantization, FP8, KV-cache management, memory efficiency, or related techniques.
Experience enabling and optimizing large language, reasoning, multimodal, or other foundation models on AI accelerators.
Experience designing distributed training or inference systems using techniques such as tensor, pipeline, expert, or sequence parallelism.
Deep knowledge of AI frameworks such as PyTorch and experience optimizing production-scale training or inference workloads.
Demonstrated experience leading complex technical initiatives across multiple engineering organizations and influencing technical strategy beyond immediate team boundaries.
Publications, patents, open-source contributions, or other recognized contributions in AI systems, distributed computing, machine learning infrastructure, or hardware acceleration.

Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

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More about this job

Responsibilities

The Principal Software Engineer will lead the technical strategy for optimizing frontier-scale AI models across Microsoft's custom AI accelerators and cloud-scale infrastructure. They will collaborate with hardware architecture teams on co-design initiatives and drive performance improvements across kernels, frameworks, and distributed systems.

Requirements

Candidates must hold a Bachelor's degree in a technical field and possess at least 6 years of engineering experience with proficiency in languages like C, C++, or Python. Strong expertise in hardware-software co-design, AI accelerator enablement, and performance optimization for large-scale workloads is required.

Skills

AI Infrastructure
Hardware-Software Co-design
Performance Optimization
Distributed Computing
Accelerator Architecture
C++
Python
CUDA
ROCm
Triton
PyTorch
Large Language Models
Quantization
Distributed Training
System Architecture
Technical Leadership

Benefits

Health Insurance
Retirement Plan
Paid Time Off
Professional Development

Visa sponsorship

Not detected in the job text

Keywords

AI Infrastructure
Hardware-Software Co-design
Azure
Performance Optimization
Distributed Computing
Accelerator Architecture
C
C++
Python
CUDA
ROCm
Triton
PyTorch
vLLM
SGLang
Large Language Models
Quantization
FP8
KV-cache
Distributed Training
System Architecture
Technical Leadership
Cloud Infrastructure
Silicon Roadmaps
Machine Learning
Software Engineering
AI Frameworks
Parallelism
Memory Management
Kernel Optimization

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