Description

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.

As an ASIC design manager, you will lead design team deliver some of the most innovative design 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 aspects

• Assess future technologies, trends, and internal innovations to drive next generation solutions

• Manage 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 requirements

• Incorporate IP from internal and external supplier, support silicom bring-up and test solutions based on your team’s designs

About the team

The Amazon Annapurna Labs team is a 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 teams 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.

We are open to hiring candidates to work out of one of the following locations:

Austin, TX, USA | Cupertino, CA, USA

Basic Qualifications

• Bachelor's degree in Electrical Engineering, related discipline, or equivalent experience

• 7+ years of experience in ASIC design and implementation with full end to end block ownership

• At least 2 cycles of design to successful silicon product, with full ASIC block or subsystem ownership

• 2+ years of management experience

Preferred Qualifications

• Master’s / PhD degree in Electrical Engineering

• Experience in development of machine learning accelerator solutions

• Good 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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $140,100/year in our lowest geographic market up to $272,400/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.