ASIC Design Engineer, Cloud-Scale Machine Learning Acceleration team

ASIC Design Engineer, Cloud-Scale Machine Learning Acceleration team

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
- integrate multiple subsystems into top level SOC, ensure correct clock/reset/functional/DFT signal routing
- As a key member of the ASIC design team, you will implement and deliver high performance, area and power efficient RTL to achieve design targets and specifications.
- Analyze design, microarchitecture or architecture to make trade-offs based on features, power, performance or area requirements.
- Develop micro-architecture, implement SystemVerilog RTL, and deliver synthesis/timing clean design with constraints.
- Perform lint and clock domain crossing quality checks on the design.
- Work with with architects, other designers, verification teams, pre- and post-silicon validation teams, synthesis, timing and back-end teams to accomplish your tasks.
You will thrive in this role if you:
- Are familiar with scripting in Python
- Are proficient with assertions
- Have good debug skills to analyze RTL test failures
- Have a "Learn and Be Curious" mindset
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

- B.S. in Electrical Engineering or related technical field
- 5+ years in RTL design for SOC
- 5+ years in VLSI engineering
- 5+ years with code quality tools including: Spyglass, LINT, or CDC

PREFERRED QUALIFICATIONS

- Master's degree in electrical engineering, computer engineering, or equivalent
- Experience with Microarchitecture, SystemVerilog RTL, Assertions, SDC constraints
- Experience with automation and scripting languages such as Python
- Familiarity with data path design, interconnects, AXI protocol
- Good analytical, problem solving, and communication skills
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,800/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit . This position will remain posted until filled. Applicants should apply via our internal or external career site.

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