ML Kernel Performance Engineer, Edge AI and Science

Benefits

Parental leave

6 weeks From the posting source checked Jun 20, 2026

Non-birth-parent leave

6 weeks From the posting source checked Jun 20, 2026

Family-building benefits

• Fertility benefits: Offered From the posting source checked Jun 20, 2026
• Adoption assistance: Offered From the posting source checked Jun 20, 2026
• Surrogacy assistance: Not verified

Mental health support

Offered From the posting source checked Jun 20, 2026

Relocation assistance

Not verified

Childcare support

Offered From the posting source checked Jun 20, 2026

Learning budget

Not verified

Verification

Source-linked checked Jun 7, 2026

Salary

CAD 115K-192K From the posting source checked Jun 20, 2026

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

U.S. benchmark only; posted salary is not compared across countries or currencies.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Company stage

Public-company From the posting source checked Jun 20, 2026

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

ML Kernel Performance Engineer, Edge AI and Science Vancouver, British Columbia, CAN Amazon Devices is an inventive research and development company that designs and engineers high-profile consumer products like the Kindle family, Fire Tablets, Fire TV, Health & Wellness devices, Amazon Echo, and Astro. We are building the next generation of edge AI capabilities through our advanced compression platform and custom neural accelerator silicon. Within Edge AI & Science, the AI Platform team builds a compression platform-the first of its kind-enabling 20-100x neural network compression for edge and cloud deployment. As model sizes grow from billions to hundreds of billions of parameters, compute efficiency becomes the single largest return on engineering investment during training. The gap between eager-mode Python and optimized GPU execution is where months of training time are won or lost. We are looking for an ML Kernel Performance Engineer to work at the hardware-software boundary of this platform, crafting high-performance CUDA and Triton kernels that make our compression algorithms run at peak efficiency during training, fine-tuning, and inference. You will build the tooling and kernel libraries that democratize GPU performance optimization across the team, enabling scientists and engineers to profile, diagnose, and fix kernel bottlenecks without needing to be CUDA experts themselves. Working alongside compression scientists and platform engineers, you will ensure that novel quantization schemes (ternary, nonary, mixed-precision) and sparse computation patterns translate into real throughput gains on GPU hardware. Your work will directly accelerate every training run in the organization and unlock deployment of compressed

Read the full description at www.amazon.jobs. FewerJobs shows a preview and links to the original posting.