What are the responsibilities and job description for the Sr. Manager ASIC, Cloud-Scale Machine Learning Acceleration team position at Amazon?
DESCRIPTION
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 customers who require specialized security solutions for their cloud services.
Annapurna Labs (our organization within AWS UC) 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.
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Custom SoCs (System on Chip) live at the heart of AWS Machine Learning servers. 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 AWS Inferentia, our custom designed machine learning inference datacenter server. Our success depends on our world-class server infrastructure; we’re handling massive scale and rapid integration of emergent technologies. We’re looking for an ASIC Design Eengineer to help us trail-blaze new technologies and architectures, while ensuring high design quality and making the right trade-offs.
Key job responsibilities
- Lead and grow a team of SOC integration engineers responsible for critical deliverables in our ML accelerator chips
- Drive technical decisions across multiple disciplines (RTL, timing, DFT, physical design)
- Ensure on-time delivery of complex SOC integration milestones
- Establish and maintain best practices for top-level integration, including clock/reset architecture, CDC methodology, and quality metrics
- Interface with various stakeholders including architecture, verification, and physical design teams
You will thrive in this role if you:
- Have a proven track record leading SOC integration teams through successful tape-outs
- Excel at cross-functional leadership and can drive complex technical decisions across multiple teams
- Are passionate about developing engineers and implementing robust integration methodologies
- Have deep expertise in high-performance SOC design, including clock/reset architecture, timing closure, and CDC methodology
- Are data-driven and can effectively balance technical excellence with project execution
About the team
Custom SoCs (System on Chip) live at the heart of AWS Machine Learning servers. 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 AWS Inferentia, our custom designed machine learning inference datacenter server. Our success depends on our world-class server infrastructure; we’re handling massive scale and rapid integration of emergent technologies. We’re looking for an ASIC Design Eengineer to help us trail-blaze new technologies and architectures, while ensuring high design quality and making the right trade-offs.
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.
BASIC QUALIFICATIONS
- 10 years of relevant industry experience with 3 years in people management
- Deep technical expertise in SOC integration and methodology
- Track record of successful tape-outs in leading edge nodes
- Strong cross-functional leadership skills
PREFERRED QUALIFICATIONS
- Master's degree in electrical engineering, computer engineering, or equivalent
- Experience with ML accelerator or high-performance compute SOC development
- Track record of implementing and scaling SOC integration methodologies
- Strong background in power/performance optimization and physical design considerations
- Experience with modern SOC development tools and flows
- Familiarity with data path design, interconnects, AXI protocol
- Good analytical, problem solving, and communication skills
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