Principal Applied Scientist, ML Codesign

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

$229K-$309K 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)

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

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

140% above the BLS role benchmark for data and ml aggregate.

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

Principal 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

Principal Applied Scientist, ML Codesign Sunnyvale, California, USA Define the joint optimization of model compression and silicon architecture for Amazon's next generation of edge and cloud inference accelerators. Your work will set the technical targets that propagate across the model, compiler, runtime, and silicon stack. We are hiring a Principal Applied Scientist to be the technical leader who closes the loop between compression science and silicon design. Today's generation ships advanced quantization and large-model distillation in production, running multi-billion parameter language models at inference economics typical of much larger systems. Future generations target significantly larger models at the edge and in the cloud. You will be a principal architect of the next-generation accelerator and of the compression algorithms it executes natively. Few roles in the industry let one technical leader influence the model, the compiler, the runtime, and the silicon without organizational friction. This is one of them. You have spent the last several years thinking about why hardware decisions and accuracy decisions live in different teams, and you want to be the person who owns both. You have published at MLSys, ISCA, MICRO, NeurIPS, or ICML on quantization, pruning, or hardware-aware training, and you want your next paper to ship in a chip rather than in a benchmark suite. You want a vertical stack-model, compression, compiler, runtime, operating system, silicon-where the same engineering organization owns every layer and a principal architect can move all of them. Key job responsibilities • Define the hardware-aware compression roadmap for next-generation accelerators, working

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