vancouver bc ai ml engineer Jobs – 133 Openings This Week

Advanced Technology: R&D Engineer - AI/ML, HPC
Cerebras Systems —Vancouver, BC
- Doctoral degree
- Computer Science
- Engineering
Systems Applications & AI Tooling Engineer (Ethernet NIC, PCIe Switch)
Broadcom —Richmond, BC
- $61,000–$98,000 a year
- Full-time
- Computer science
- Computer Science
- DevOps
- Employee stock purchase plan
- Dental care
AI/Machine Learning Engineer
Armstrong Collective —Vancouver, BC
- $125,000–$145,000 a year
- Hybrid work
- Azure
- AWS
- Machine learning
- Disability insurance
- Dental care
AI Staff Machine Learning Engineer, General AI, ML & Big Data
C-Serv —Vancouver, BC
- Hybrid work
- Computer science
- Azure
- Doctoral degree
- Dental care
- Paid time off
Quick apply
Sr. AI Engineer - Player Intelligence and Growth, Data & Insights (D&I)
Electronic Arts —Vancouver, BC
- $122,300–$170,700 a year
- Full-time
- Hybrid work
- Computer science
- Computer Science
- Engineering
- Disability insurance
- Dental care
ML Kernel Performance Engineer, Edge AI and Science
Amazon Development Centre Canada ULC —Vancouver, BC
- $114,800–$191,800 a year
- Full-time
- Computer Science
- Java
- AWS
- Profit sharing
- Dental care
1d
Senior AI Engineer / Architect
D3 Security Management Systems —Vancouver, BC
- Full-time
- Azure
- SQL
- APIs
- Dental care
Quick apply
Principal Engineer, AI & ML Solutions
Royal Bank of Canada —Vancouver, BC
- Full-time
- APIs
- AI
- Python
RPA and Agentic AI Engineer
Vancouver City Savings Credit Union —Vancouver, BC
- $101,200–$124,950 a year
- Overtime
- Hybrid work
- Azure
- DevOps
- Databases
- Designated paid holidays
- Dental care
AI Software Engineer
Alexander College —Vancouver, BC
- $100,000 a year
- Weekends as needed
- Computer science
- Azure
- Computer Science
- Dental care
- Paid time off
Quick apply
13d
SDET (Full Stack), Creativity Apps
Apple —Vancouver, BC
- $116,800–$226,000 a year
- Computer Science
- Project management
- Bachelor's
- Employee stock purchase plan
- Dental care
14d
Data Engineer
Remarcable, Inc. —Vancouver, BC
- $130,000–$150,000 a year
- Full-time
- Hybrid work
- SQL
- AWS
- Python
Data Scientist
University of British Columbia —Vancouver, BC
- $7,622.83–$11,886.67 a month
- Full-time
- Java
- Master's degree
- SQL
7d
Staff R&D Engineer-17397
Synopsys —Vancouver, BC
- $100,000–$150,000 a year
- Doctoral degree
- Master's degree
- C++
13d
Forward Deployed AI Engineer
Nucleus —Vancouver, BC
- $120,000–$150,000 a year
- Full-time
- Hybrid work
- Computer Science
- Engineering
- Databases
Quick apply
13d
Data Scientist
UBC Faculty of Forestry —Vancouver, BC
- $7,622.83–$11,886.67 a month
- Full-time
- Java
- Master's degree
- SQL
7d
Research Intern - AI Hardware
Microsoft —Vancouver, BC
- $5,600–$10,000 a month
- Doctoral degree
- Computer Science
- Engineering
AI Software Engineer
TrustFlight —Vancouver, BC
- $110,000–$160,000 a year
- Full-time
- Computer Science
- CAD
- Engineering
- Dental care
- Paid time off
Quick apply
Machine Learning Engineer - Evisort
Workday —Vancouver, BC
- $128,000–$192,000 a year
- Full-time
- Doctoral degree
- Computer Science
- Engineering
Algorithm Engineer, AI
Comm100 Network Corporation —Vancouver, BC
- $80,000–$120,000 a year
- Computer Science
- Databases
- Analysis skills
- Dental care
Quick apply

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ai ml engineer jobs near vancouver bc

Advanced Technology: R&D Engineer - AI/ML, HPC

Cerebras Systems
Vancouver, BC

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Job details

Qualifications

Doctoral degree
Computer Science
Applied Mathematics
Engineering
Mathematics
Master's degree
C
Physics
AI
Communication skills
Python

Full job description

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.

Cerebras' current customers include top 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.

Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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.

About The Team

Cerebras builds wafer-scale AI processors—single chips delivering tens of PB/s of memory bandwidth and a dataflow architecture that accelerates at a granularity no multi-device system can match. The Advanced Technology Group (ATG) is Cerebras’ pathfinding organization. We work ahead of product to explore new architectures, demonstrate breakthrough performance on scientific and AI workloads, and shape the technical roadmap for future Cerebras hardware and software. Our work regularly appears at top-tier venues (Supercomputing, SIAM, IEEE, and NeurIPS) and directly influences the design of next-generation wafer-scale systems.

About The Role

We are seeking R&D Engineers to join Cerebras' Advanced Technology Group. You will design and implement workloads that establish new performance benchmarks on wafer-scale hardware, leveraging architectural features that no traditional platform offers. The
scope ranges from large-scale scientific simulations to emerging AI/ML models, and the work sits at the intersection of algorithm design, compiler co-optimization, and hardware architecture. You will collaborate closely with Cerebras’ ASIC, compiler, kernel, and AI teams as well as external partners at universities and national laboratories.

What You Will Do

Design and implement challenging scientific computing and AI workloads on Cerebras’ Wafer-Scale Engine, targeting performance results that advance the state of the art.
Lead algorithm–hardware co-design efforts with internal R&D teams and external research partners, turning architectural capabilities into measurable application-level advantages.
Build analytical performance models that quantify bottlenecks, guide optimization, and inform future chip and compiler design decisions.
Contribute to Cerebras’ multi-year technology roadmap by identifying high-impact workloads, proposing architectural experiments, and validating them on silicon.
Publish findings and present at top-tier conferences and journals; represent Cerebras in the broader HPC and AI research communities.

What We Are Looking For

PhD in Computer Science, Engineering, Applied Mathematics, Physics, or a related quantitative field preferred. Exceptional candidates without a graduate degree who demonstrate equivalent depth through published research, significant open-source contributions, or a strong industry track record are encouraged to apply.
Deep experience in at least one of the following: computer architecture and accelerator design; parallel, distributed, or high-performance computing; numerical methods and scientific simulation; AI/ML theory and model design at a mathematical level.
Strong ability to analytically model and optimize the performance of complex systems and algorithms.
Track record of published research or patents in relevant venues.
Proficiency in C and Python; comfort working close to hardware.
Excellent communication and interpersonal skills: able to present complex technical material to both specialist and cross-functional audiences, and to collaborate effectively in a fast-paced, small-team environment.

Areas Of Particular Interest

We are hiring across several focus areas. Exceptional depth in one or more of the following is a strong signal:

Computational science: researchers who can bring insights from numerical methods and simulation into AI, or couple simulation and learning into joint computational workflows. Depth in hydrodynamics, solid mechanics, electromagnetics, molecular dynamics, or related PDE-based fields.
AI/ML foundations: deep understanding of model architecture, optimization methods, and their statistical underpinnings—the ability to design from first principles, not just apply established recipes.
Computer architecture: microarchitecture design, computing paradigms at the circuit and datapath level, memory hierarchy design.
Performance engineering: roofline modeling, bandwidth analysis, kernel optimization, communication-computation overlap, and compiler-level tuning for novel hardware.

Why This Opportunity Is Exciting And Unique

Build on a fundamentally different architecture, unconstrained by GPU assumptions.
Publish and open-source your research. We present at Supercomputing, SIAM, IEEE, NeurIPS, and beyond.
Work on the fastest AI system in the world, with direct access to the hardware your compiler targets.
Join at a pivotal moment: Cerebras is pre-IPO with strong commercial traction and rapid growth.
Be part of a small, technical team with high autonomy, minimal bureaucracy, and a culture that values depth over hierarchy.

We are hiring for multiple positions across experience levels. If this work resonates, we encourage you to apply.

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.

Apply Now

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ai ml engineer jobs in vancouver bc

Advanced Technology: R&D Engineer - AI/ML, HPC

Systems Applications & AI Tooling Engineer (Ethernet NIC, PCIe Switch)

AI/Machine Learning Engineer

AI Staff Machine Learning Engineer, General AI, ML & Big Data

Sr. AI Engineer - Player Intelligence and Growth, Data & Insights (D&I)

ML Kernel Performance Engineer, Edge AI and Science

Senior AI Engineer / Architect

Principal Engineer, AI & ML Solutions

RPA and Agentic AI Engineer

AI Software Engineer

SDET (Full Stack), Creativity Apps

Data Engineer

Data Scientist

Staff R&D Engineer-17397

Forward Deployed AI Engineer

Data Scientist

Research Intern - AI Hardware

AI Software Engineer

Machine Learning Engineer - Evisort

Algorithm Engineer, AI

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