Amazon
Sr. SDE, Chip Validation Ops, Annapurna Labs Machine Learning Acceleration
Amazon, Austin, Texas, us, 78716
Overview
Sr. SDE, Chip Validation Ops, Annapurna Labs Machine Learning Acceleration AWS (Amazon Web Services). The role involves designing and implementing software systems to monitor, test, and improve silicon quality across our fleet, and building scalable solutions for tracking component performance and automating quality inspection processes. Description AWS Utility Computing (UC) provides product innovations from foundational services such as Amazons Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWSs services and features apart in the industry. As a member of the UC organization, youll 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. Custom machine learning chips are at the heart of our Trainium machine learning instances, and we invite you to build them with us! Responsibilities
Develop and maintain systems to track silicon part quality metrics Create and scale functional, performance, logic and electrical tests Design and scale automated inspection mechanisms for quality control Collaborate with hardware teams to define test requirements and specifications Basic Qualifications
Bachelor's degree in Computer Science, Computer Engineering, or related field 8+ years of chip design and/or embedded development experience Experience with test automation and continuous integration Knowledge of semiconductor testing methodologies Proficiency in one or more programming languages (C++, Python, Java) Experience with large-scale distributed systems Preferred Qualifications
Knowledge of hardware description languages (Verilog, VHDL) Background in test development for semiconductor devices Experience with statistical analysis and data visualization Familiarity with hardware debugging tools 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, please visit the AWS accommodations page for more information. #J-18808-Ljbffr
Sr. SDE, Chip Validation Ops, Annapurna Labs Machine Learning Acceleration AWS (Amazon Web Services). The role involves designing and implementing software systems to monitor, test, and improve silicon quality across our fleet, and building scalable solutions for tracking component performance and automating quality inspection processes. Description AWS Utility Computing (UC) provides product innovations from foundational services such as Amazons Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWSs services and features apart in the industry. As a member of the UC organization, youll 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. Custom machine learning chips are at the heart of our Trainium machine learning instances, and we invite you to build them with us! Responsibilities
Develop and maintain systems to track silicon part quality metrics Create and scale functional, performance, logic and electrical tests Design and scale automated inspection mechanisms for quality control Collaborate with hardware teams to define test requirements and specifications Basic Qualifications
Bachelor's degree in Computer Science, Computer Engineering, or related field 8+ years of chip design and/or embedded development experience Experience with test automation and continuous integration Knowledge of semiconductor testing methodologies Proficiency in one or more programming languages (C++, Python, Java) Experience with large-scale distributed systems Preferred Qualifications
Knowledge of hardware description languages (Verilog, VHDL) Background in test development for semiconductor devices Experience with statistical analysis and data visualization Familiarity with hardware debugging tools 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, please visit the AWS accommodations page for more information. #J-18808-Ljbffr