Software Engineer- AI/ML, AWS Neuron Distributed Training - Performance Optimization

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

$144K-$194K 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

45% above the BLS role benchmark for software engineering aggregate.

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

Growth-stage 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

Software Engineer- AI/ML, AWS Neuron Distributed Training - Performance Optimization Seattle, Washington, USA Annapurna Labs designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago-even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world. AWS Neuron is the complete software stack for the AWS Trainium and Inferentia cloud-scale machine learning accelerators and the Trn3/Trn2/Trn1 and Inf2/Inf1 servers that use them. This role is for a software engineer in the Distributed Training team for AWS Neuron. This role is responsible for development, enablement and performance tuning of a wide variety of ML model families, including massive scale multi-modal large language models like Llama, Qwen, gpt-oss, DeepSeek and beyond, as well as multi-modal generation models such as Stable Diffusion, Flux, WAN, and many more. The Distributed Training team works side by side with chip architects, compiler engineers and runtime engineers to create, build and tune distributed training solutions with AWS Trainium, maximize training throughput, minimize time-to-convergence, and push the boundaries of training efficiency on Trainium. You will identify and resolve performance bottlenecks across the stack, from collective communications and memory utilization to compiler optimizations and kernel performance. Key job responsibilities This role will help lead efforts to optimize distributed training performance on Trainium, with a primary focus on maximizing training throughput, model flops utilization, and efficiency

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