Jobs in Vaughan, ON and nearby (72,193 jobs)

Jobs within 25 km of Vaughan, ON, Canada. Nearby towns and cities are included. Distances are straight-line, not driving distances.

72,193 listings · 9,729 employers Counted Nov 14, 2026. How we count

About these jobs

Employers hiring include Husky Technologies (1,704 listings), Loblaw Companies Limited (1,686 listings), Shoppers Drug Mart (1,097 listings).

Common roles: Software engineer, Project manager, Retail sales associate.

11,717 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	90,000.00	6,594
CAD / hour	26.00	4,805
USD / year	159,000.00	60
CAD / week	1,650.00	31
CAD / month	6,000.00	28
CAD / day	101.00	13

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: 0% remote, 26% hybrid, 74% 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

Jobs in Vaughan, ON and nearby

Within 25 km

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Cerebras Systems

Full Stack LLM Engineer

Toronto, ON, Canada

Apply on jobs.ashbyhq.com About employer

Applications open in a new tab.

Job details

Posting language: English
Posted: Jul 18, 2025

Original job description

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.

This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.

Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.

About the Role
We are seeking a versatile and experienced engineer to join our Inference Core Model Bringup team. This team is responsible to rapidly bring up state-of-the-art open-source models (like LLaMA, Qwen, etc) or customer-provided proprietary models on our Cerebras CSX systems. Success in this role requires a system-minded generalist who thrives in fast-paced bringup environments and is comfortable working across the entire Cerebras software stack.
Your work will play a critical role in achieving unprecedented levels of performance, efficiency, and scalability for AI applications.

Responsibilities

Contribute to the end-to-end bring up of ML models on Cerebras CSX systems.
Work across the stack: model architecture translation, graph lowering, compiler optimizations, runtime integration, and performance tuning.
Debug performance and correctness issues spanning model code, compiler IRs, runtime behavior, and hardware utilization.
Propose and prototype improvements across tools, APIs, or automation flows to accelerate future bring ups.

Skills & Qualifications

Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field.
Comfort navigating the full AI toolchain: Python modeling code, compiler IRs, performance profiling, etc.
Strong debugging skills across performance, numerical accuracy, and runtime integration.
Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and familiarity with model internals (e.g., attention, MoE, diffusion).
Proficiency in C/C++ programming and experience with low-level optimization.
Proven experience in compiler development, particularly with LLVM and/or MLIR.
Strong background in optimization techniques, particularly those involving NP-hard problems.

What We Offer

Competitive salary and benefits package.
Opportunities for professional growth and career advancement.
A dynamic and innovative work environment.
The chance to work on cutting-edge technologies and make a significant impact on the future of AI.

Why Join Cerebras

People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:

Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.

Find out more about what it's like to work at Cerebras here!

Apply today and become part of the forefront of groundbreaking advancements in AI!

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Apply on jobs.ashbyhq.com About employer

More about this job

Responsibilities

The Full Stack LLM Engineer at Cerebras Systems will bring machine learning models up end to end on Cerebras hardware. They will work across the software stack, from model code and compilers to runtime and performance, and debug issues that span them.

Requirements

Candidates need a degree in computer science, engineering or a related field, plus experience with deep learning frameworks, C/C++ low-level optimization and compiler development such as LLVM or MLIR. Strong debugging and optimization skills, including work on NP-hard problems, are also expected.

Skills

Python
C
C++
PyTorch
TensorFlow
LLVM
MLIR
Compiler optimization
Performance profiling
Debugging
Low-level optimization
Model architecture
Graph lowering
Runtime integration
Numerical accuracy
Optimization algorithms
NP-hard problems
Deep learning
Attention mechanisms
Mixture of Experts
Diffusion models
Hardware utilization

Benefits

Professional growth and career advancement

Keywords

LLM
machine learning
model bringup
PyTorch
TensorFlow
C++
C
LLVM
MLIR
compiler development
performance profiling
inference
deep learning
attention
MoE
diffusion
NP-hard optimization
runtime integration
full stack
AI hardware

Department

software_development

Tools

PyTorch
TensorFlow
LLVM
MLIR
C++

Languages

English

Fields of study

Computer Science
Engineering

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Work requirements

Jobs in Vaughan, ON and nearby