AWS Intern
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Job Description
About Company:
• Lensa: The leading career site for job seekers at every stage of their career.
• Amazon: The client for whom Lensa is advertising this internship opportunity. Specifically, this role is within Amazon Web Services (AWS) in the Annapurna Labs division.
Job Description:
This is a full-time (40 hours/week) internship for 12 consecutive weeks during the summer within Amazon Web Services (AWS), specifically in the Annapurna Labs team working on Cloud-Scale Machine Learning Acceleration. As a member of the Cloud-Scale Machine Learning Acceleration team you’ll be responsible for the design and optimization of Software and Hardware in our data centers including technologies such as AWS Inferentia, which is a machine learning inference accelerator designed to deliver high performance at low cost.
Key Responsibilities:
• Perform physical design for Amazon’s machine learning custom silicon solutions.
• Participate in various aspects of physical design: full chip floorplanning, circuit analysis, power/clock distribution, timing optimization, place and route, power integrity analysis, and physical verification.
• Write Tcl or PERL scripts to improve physical design flows and methods.
• Collaborate with RTL, DFT designers to ensure high quality design implementation.
Basic Qualifications:
• Enrolled in a Bachelors’ degree program or higher in Electrical Engineering, Computer Engineering, or a related field with a graduation conferral date between December 2025 and September 2026
• Scripting internship/project experience with Python, Perl or equivalent
• Strong understanding of VLSI circuit design fundamentals
• Have taken at least one or more VLSI circuit design and implementation classes and done lab projects
Preferred Qualifications:
• Enrolled in a Master’s degree program in Electrical Engineering or Computer Engineering
• Previous relevant technical internship experience
• Experience with FinFET design, Clock/Power Distribution, Spice Circuit analysis
• Experience with Place and Route, digital implementation
• Experience with EDA tools from Synopsys (ICC2, DC, PT), Cadence (Genus, Innovus, Voltus)
• Experience with Verilog/SystemVerilog
