SDE, MLA hardware/software co-design, Annapurna Labs Machine Learning Acceleration

Amazon is hiring an SDE, MLA hardware/software co-design, Annapurna Labs Machine Learning Acceleration in Austin, United States. It pays $154k-$215k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
The posting mentions AWS, embedded software and system development among its tools and skills.
Level classes it as a senior role.
Amazon has 20,000+ other open roles on Level.

AI in this role

Software Development Engineer focusing on pre-silicon hardware/software co-design and verification for machine learning acceleration chips.

AWS

embedded-softwaresystem-developmentchip-designhardware-software-co-designmachine-learning-acceleration

As an SDE in the pre-silicon team, you will be responsible for driving the pre-silicon hardware/software co-development for our machine learning chips.

You will work with architecture, design and emulation teams to build new silicon functionality.

You will write bare-metal software to verify the end-to-end functionality of the SoC and the functionality and performance of different subsystems in the SoC.

If you have a solid background in embedded software, system development or chip design, come join us!

About the team
Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Utility Computing (UC)
AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.

Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Basic qualifications

- Bachelor's degree in Electrical Engineering or a related field
- Experience identifying bugs in architecture, algorithms, functionality, and performance with strong overall debugging skills
- Experience verifying at multiple levels of logic from IP blocks to SoCs to full system testing

Preferred qualifications

- Master's degree in Electrical or Communications Engineering or a related field
- Experience with formal verification techniques including abstraction and end-to-end checking
- Experience with industry standard tools and scripting languages (Python or Perl) for automation

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, TX, Austin - 153,600.00 - 215,000.00 USD annually

How we rate this

SDE, MLA hardware/software co-design, Annapurna Labs Machine Learning Acceleration at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

SDE, MLA hardware/software co-design, Annapurna Labs Machine Learning Acceleration is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $154k-$215k a year.
The role is based in US, TX, Austin.
The job was posted on July 28, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Embedded SoftwareSystem DevelopmentChip DesignHardware Software Co DesignMachine Learning AccelerationAWS

Also common in software engineer jobs at this level

LLM C++AI agents Kubernetes Java Generative AI

Pay

This job starts at: $154k
Typical software engineer job: $167k

This posting starts 8% below the typical software engineer job. See software engineer jobs

Questions you could be asked

Tell me about a project where embedded software was part of your work. What did you do?
Tell me about a project where system development was part of your work. What did you do?
Tell me about a project where chip design was part of your work. What did you do?
Tell me about a project where hardware software co design was part of your work. What did you do?
Tell me about a project where machine learning acceleration was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Embedded Software, System Development, Chip Design, Hardware Software Co Design, and Machine Learning Acceleration. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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