Applied Scientist, 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

Not verified

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)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

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

Role

Role function

Data 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

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

Applied Scientist, Edge AI and Science Cambridge, England, GBR Amazon Devices is an inventive research and development company that designs and engineers high-profile devices like the Kindle family of products, Fire Tablets, Fire TV, Health & Wellness, Amazon Echo, and Astro products. This is an exciting opportunity to bring generative AI to Amazon's consumer products, both on-device at the edge and in the cloud. Our compression platform delivers 20x to 100x neural network compression, but using it well still takes weeks of hands-on learning and expert intuition. The Edge AI Model Studio team exists to change that. We become the expert users so partner teams don't have to: we turn compression science into reliable, production workflows, and we package the results into a library of compression-ready student architectures that partners can run on their own. Our north star is simple. Training-to-deployment should feel like pushing a button, not a month-long science project. We are looking for an Applied Scientist to join Model Studio and help compress the next generation of models for edge and cloud deployment across modalities, including large language models, vision-language models, speech and audio models, and omni models that reason jointly over text, audio, and video. You will apply and extend state-of-the-art compression recipes to real models, define the benchmarks and evaluation methodology that make trade-offs explicit, and build the reference implementations that let other teams deploy compressed models without our help. You will work backwards from deployment constraints such as memory, latency, throughput, power, and cost,

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