Amazon
ASIC Design Manager
Amazon, Cupertino, California, United States, 95014
AWS Machine Learning accelerators are at the forefront of AWS innovation. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium will deliver the best-in-class ML training performance with the most teraflops (TFLOPS) of compute power for ML in the cloud. This is all enabled by cutting edge software stack, the AWS Neuron Software Development Kit (SDK), which includes an ML compiler, runtime and natively integrates into popular ML frameworks, such as PyTorch, TensorFlow and MxNet. AWS Neuron and Inferentia are used at scale with customers like Snap, Autodesk, Amazon Alexa, Amazon Rekognition and more customers in various other segments.
Check below to see if you have what is needed for this opportunity, and if so, make an application asap.As an ASIC design manager, you will lead design team deliver some of the most innovative designs in the cutting edge machine learning accelerator projects. You will lead the development effort on advanced machine learning accelerator systems, own end to end delivery. You will also assess future technologies, trends, and internal innovations to drive next generation solutions.
Key job responsibilities In this role you will:develop advanced machine learning accelerator systems, own end to end microarchitecture and design aspectsAssess future technologies, trends, and internal innovations to drive next generation solutionsManage microarchitecture and design team with full responsibility for hiring and developing best talent and delivering team’s results.Work closely with software, verification and physical design teams to deliver high quality designs that meet performance, power and area requirementsIncorporate IP from internal and external suppliers, support silicon bring-up and test solutions based on your team’s designs
About the team The Amazon Annapurna Labs team is responsible for building innovation in silicon and software for AWS customers. We are at the forefront of innovation by combining cloud scale with the world’s most talented engineers. Our team covers multiple disciplines including silicon engineering, hardware design and verification, software and operations. Because of our team's breadth of talent, we have been able to improve AWS cloud infrastructure in networking and security with products such as AWS Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), in compute with AWS Graviton and the EC2 F1 FPGA instances, in storage with scalable NVMe, and now in AI and Machine Learning with AWS Neuron SDK, Inferentia and Trainium ML accelerators.
BASIC QUALIFICATIONS
Bachelor's degree in Electrical Engineering, related discipline, or equivalent experience7+ years of experience in ASIC design and implementation with full end to end block ownershipAt least 2 cycles of design to successful silicon product, with full ASIC block or subsystem ownership2+ years of management experience
PREFERRED QUALIFICATIONS
Master’s / PhD degree in Electrical EngineeringExperience in development of machine learning accelerator solutionsGood analytical, problem solving, and communication skills
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.
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Check below to see if you have what is needed for this opportunity, and if so, make an application asap.As an ASIC design manager, you will lead design team deliver some of the most innovative designs in the cutting edge machine learning accelerator projects. You will lead the development effort on advanced machine learning accelerator systems, own end to end delivery. You will also assess future technologies, trends, and internal innovations to drive next generation solutions.
Key job responsibilities In this role you will:develop advanced machine learning accelerator systems, own end to end microarchitecture and design aspectsAssess future technologies, trends, and internal innovations to drive next generation solutionsManage microarchitecture and design team with full responsibility for hiring and developing best talent and delivering team’s results.Work closely with software, verification and physical design teams to deliver high quality designs that meet performance, power and area requirementsIncorporate IP from internal and external suppliers, support silicon bring-up and test solutions based on your team’s designs
About the team The Amazon Annapurna Labs team is responsible for building innovation in silicon and software for AWS customers. We are at the forefront of innovation by combining cloud scale with the world’s most talented engineers. Our team covers multiple disciplines including silicon engineering, hardware design and verification, software and operations. Because of our team's breadth of talent, we have been able to improve AWS cloud infrastructure in networking and security with products such as AWS Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), in compute with AWS Graviton and the EC2 F1 FPGA instances, in storage with scalable NVMe, and now in AI and Machine Learning with AWS Neuron SDK, Inferentia and Trainium ML accelerators.
BASIC QUALIFICATIONS
Bachelor's degree in Electrical Engineering, related discipline, or equivalent experience7+ years of experience in ASIC design and implementation with full end to end block ownershipAt least 2 cycles of design to successful silicon product, with full ASIC block or subsystem ownership2+ years of management experience
PREFERRED QUALIFICATIONS
Master’s / PhD degree in Electrical EngineeringExperience in development of machine learning accelerator solutionsGood analytical, problem solving, and communication skills
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.
#J-18808-Ljbffr