Job Location: Cupertino, CA
- BS degree or higher in EE, CE, or CS
- 8+ years of practical verification experience, either using formal engines or simulators
- 5+ years of practical experience with formal verification as IP/Block owner
- 5+ years of experience with formal verification techniques including abstraction and end-to-end checking
- Experience with System Verilog, System Verilog Assertion Language (SVA), or equivalent
- Excellent verbal and written communication skills
As a member of the Cloud-Scale Machine Learning Acceleration team you’ll be responsible for the design and optimization of hardware in our data centers including technologies such as AWS Trainium which is a machine learning inference & training product designed to deliver high performance at low cost.
Key job responsibilities
- Develop formal verification plans, implement and verify state-of-the-art IP architectures
- Work with block designers to gain deep micro-architectural understanding
- Develop checking algorithms, assertions, and FV models
- Perform state of the art formal methods and abstraction techniques
- Participate in test plan and coverage reviews
- Promote assertions to simulation and contribute to overall simulation strategy
- Communicate and work with team members across multiple disciplines
A day in the life
It’s never a dull-day at AWS, it’s always Day 1! What that means is that our team operates in a big startup mode all the time. We constantly review our priorities to deliver the highest quality products to our customers. This involves doing deep-dives on our architecture, micro-architecture and validating the products and features. Everyone in our team is a leader, that means you will be responsible for not only developing and debugging fails, but also working closely with the stakeholders and re-balancing your work as needed. Being flexible, nimble and making quick decisions is encouraged
About the team
MLA team is located in Austin, TX and Cupertino, CA. The team has delivered multiple successful products and is developing industry leading ML training and inference solutions, while working as a startup. Team members make fast, informed decisions collaborating closely with all functions while continuously challenging each other to work smarter, do only what’s necessary and not bogged down by elaborate processes. If you’re dynamic, not afraid to take risks and roll-up your sleeves to work with a team of motivated engineers, this is the place for you!!
- MS degree in EE, CE or CS
- Strong understanding of u-arch design comprehension and debugging
- Profound understanding of formal verification engines and bug hunting strategies
- Strong programming and scripting skills
- Practical experience with RTL design
- Motivated and self-driven, takes initiative to constantly improve design, micro-architecture and architecture working with the right stakeholders
- Meets/exceeds Amazon’s leadership principles requirements for this role
- Meets/exceeds Amazon’s functional/technical depth and complexity for this role
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
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