Machine Learning - Compiler Engineer II, Annapurna Labs

Benefits

Parental leave

Not verified not verified - source not recorded; timestamp not recorded

Non-birth-parent leave

Not verified not verified - source not recorded; timestamp not recorded

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified

Salary

Not verified not verified - source not recorded; timestamp not recorded

401(k) match

Not verified

Was this benefit information wrong? Tell us.

Schedule

Shift type

Not verified

Weekend work

Not verified

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Machine Learning - Compiler Engineer II, Annapurna Labs Seattle, Washington, USA The Product: AWS Machine Learning accelerators are at the forefront of AWS innovation and one of several AWS tools used for building Generative AI on AWS. 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. The Team: As a whole, the Amazon Annapurna Labs team is responsible for silicon development at AWS. The team covers multiple disciplines including silicon engineering, hardware design and verification, software and operations. The AWS Neuron team works to optimize the performance of complex neural net models on our custom-built AWS hardware. More specifically, the AWS Neuron team is developing a deep learning compiler stack that takes neural network descriptions created in frameworks such as TensorFlow, PyTorch, and MXNET, and converts them into code suitable for execution. As you might expect, the team is comprised of some of the brightest minds in the engineering, research, and product communities, focused on the ambitious goal of creating a toolchain that will provide

Read the full description at www.amazon.jobs. FewerJobs shows a source-linked preview and links to the original posting.