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Added 3 mins ago
DevOps Manager
Rightsline Inc
Toronto, ON
$85,000 to $95,000 CAD / year
Rightsline is hiring a DevOps Manager, based in Toronto, to lead the team that owns our cloud platform, delivery pipelines, and production reliability across North America and Europe. You…
Added 18 mins ago
Quality Engineer Manager, TD Securities
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Full-time
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Added 33 mins ago
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Sr AI Developer Platform/ Platform Engineering
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Added 1 hour ago
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Senior Software Engineer (Salesforce) - Specialty Health Technology
Added 1 hour ago
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Added 1 hour ago
AI Engineer, Agent Product (Full-time/Part-time) (Canada)
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Full-time · Part-time
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Added 1 hour ago
Software Engineer, Payments and Revenue
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Richmond Hill, ON
$150,000 to $180,000 CAD / year
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Added 1 hour ago
Principal Software Engineer, Full-Stack Development
Zynga
Toronto, ON
$118,300 to $168,300 CAD / year
…company's games - Central Technology! As a Principal Software Engineer, you will be responsible for the technical vision, design and implementation of AI-powered tools and systems that…
Added 1 hour ago
ML Runtime and Kernel Engineer - Core ML
Cerebras
Toronto, ON
Full-time
We are looking for an engineer to bridge the gap between promising research ideas and efficient execution on Cerebras systems. You will work across ML frameworks, compilers, runtimes, and…
Added 2 hours ago
Intermediate Tier 3 Support Engineer
JSI
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Added 2 hours ago
Software Engineer II, Organizations (Auth0)
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Added 2 hours ago
Senior Manager, Data Services & Platforms
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Added 2 hours ago
Product Engineer
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DevOps Engineer
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Added 2 hours ago
Senior Design Engineer
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Added 3 hours ago
Senior Engineer - ServiceNow Development
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Mississauga, ON · CAN Home Office Mississauga ON
$87,780 to $122,892 CAD / year
Full-time
We’re looking for a Senior Engineer - ServiceNow Development to play a key role in designing and delivering innovative ServiceNow solutions that enhance service management processes and…
Added 3 hours ago
AI Deployment & Solutions Engineer
Tata Consultancy Services
Toronto, ON
Full-time
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Added 4 hours ago
Machine Learning Engineer - Multiple Positions
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Full-time
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Added 4 hours ago
Manager - Release, Configuration & Environment Management
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…partnering closely with Development, QA, Security, Infrastructure, Platform Engineering, DevOps, and business…
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Identity Security Engineer – Non-Human & AI Agent Identity
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Direct experience with Workload Identity Federation (WIF) across at least one major cloud platform: GCP, Azure, or AWS.

Cerebras

ML Runtime and Kernel Engineer - Core ML

Toronto, ON, Canada

Job type: Full-time
Apply by: Oct 28, 2026
Posting language: English
Posted: Sep 28, 2026

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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

The Core ML team develops novel machine learning algorithms that take advantage of the unique capabilities of the Cerebras Wafer-Scale Engine. Our work spans efficient LLM training and inference, parallel and diffusion-based generation, sparsity, scaling laws, and training dynamics.

We are looking for an engineer to bridge the gap between promising research ideas and efficient execution on Cerebras systems. You will work across ML frameworks, compilers, runtimes, and low-level kernels to implement new algorithmic capabilities, diagnose performance bottlenecks, and turn research prototypes into robust, high-performance demonstrations.

Depending on your background, your work may emphasize runtime capabilities such as token orchestration, scheduling, communication, and distributed execution; low-level kernel development for novel ML operations; or a combination of both.

Responsibilities

Design and implement runtime components and high-performance kernels required by novel Core ML algorithms.
Translate research prototypes into efficient implementations for the Cerebras platform, including reference implementations and comparisons on GPUs where useful.
Profile and debug performance across the ML framework, compiler, runtime, communication, and kernel layers.
Optimize computation, memory movement, communication, and concurrency for large-scale training and low-latency inference.
Develop benchmarks, instrumentation, and automated tests that validate functionality, performance, and numerical correctness.
Collaborate closely with Core ML researchers and compiler, runtime, kernel, and inference engineers to evaluate design alternatives and deliver end-to-end capabilities.
Contribute to software architecture and roadmap decisions by identifying recurring limitations and high-leverage platform improvements.

Skills & Qualifications

Bachelor’s, Master’s, PhD, or equivalent practical experience in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
Experience developing high-performance systems software, ML systems, runtimes, compilers, or computational kernels.
Strong programming skills in C++ and Python.
Solid understanding of parallel programming, memory management, concurrency, data structures, and performance optimization.
Proven ability to debug and profile complex software across multiple layers of a system.
Familiarity with modern machine learning architectures and frameworks such as PyTorch or JAX.
Ability to work effectively with researchers and translate evolving algorithmic requirements into reliable software.

Preferred Skills & Qualifications

Experience with CUDA, Triton, low-level assembly, accelerator programming, or a C-like domain-specific language.
Experience with compiler internals, distributed runtimes, custom hardware interfaces, or HPC systems.
Understanding of machine learning fundamentals and ML systems, with the ability to reason about how algorithmic choices affect accuracy, systems implementation and performance.
Familiarity with LLM training or inference, including attention, KV-cache management, parallel generation, or distributed execution.
Experience developing software in an industrial or academic research environment where requirements evolve through experimentation.
Contributions to significant open-source systems, ML frameworks, compilers, or kernel libraries.

Why Join Cerebras

About

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.

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More about this job

Responsibilities

Design and implement runtime components and high-performance kernels for Core ML algorithms, translating research prototypes into efficient Cerebras implementations. Profile and optimize performance across frameworks, compilers, runtimes, communication, and kernels, while developing benchmarks and collaborating across research and engineering teams.

Requirements

Candidates need a degree or equivalent practical experience in a relevant engineering or computer science field, experience with high-performance systems software, ML systems, runtimes, compilers, or kernels, and strong C++ and Python skills. They should understand parallel programming and performance optimization, be able to debug complex systems, and be familiar with modern ML architectures and frameworks such as PyTorch or JAX.

Skills

C++
Python
High-Performance Systems Software
Machine Learning Systems
Runtime Development
Compiler Development
Computational Kernels
Parallel Programming
Memory Management
Concurrency
Performance Optimization
Profiling And Debugging
PyTorch
JAX
Accelerator Programming
Distributed Execution

Visa sponsorship

Not detected in the job text

Keywords

Cerebras Wafer-Scale Engine
C++
Python
PyTorch
JAX
Machine Learning
Large Language Models
LLM Training
LLM Inference
Runtime Systems
Compiler Internals
Computational Kernels
CUDA
Triton
Low-Level Assembly
Accelerator Programming
Parallel Programming
Distributed Runtimes
Distributed Execution
High-Performance Computing
Memory Management
Concurrency
Performance Profiling
Performance Optimization
Attention
KV-Cache Management
Parallel Generation
Communication
Numerical Correctness
Benchmarking

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