Description
The Product:
AWS Machine Learning accelerators are at the forefront of cloud innovation and power some of the most advanced Generative AI applications on AWS. Our custom silicon – including the Inferentia chip for ML inference and the Trainium chip for ML training – delivers industry-leading performance and cost efficiency at scale. These are powered by the AWS Neuron Software Development Kit (SDK), which includes a deep learning compiler, runtime, and native integration with popular ML frameworks like PyTorch, TensorFlow, and MXNet.
Customers such as Snap, Autodesk, Amazon Alexa, and Amazon Rekognition are already benefiting from this technology at scale – and we’re just getting started.
The Opportunity – Tel Aviv
We're excited to expand the AWS Neuron team to a new engineering site in Tel Aviv. This is a unique opportunity to be part of the founding team, shaping our culture and technical direction locally while contributing to a global mission. The Tel Aviv team will play a key role in developing the Neuron compiler stack – translating high-level neural network models into high-performance execution on AWS custom hardware.
Key job responsibilities
The Team
As part of Amazon Annapurna Labs, the AWS Neuron team spans software, hardware, and silicon engineering disciplines. We work closely with AWS service teams and contribute directly to the performance and scalability of ML workloads across the cloud. Our focus: creating a robust, high-performance toolchain that accelerates innovation in Generative AI.
You
As a Senior Machine Learning Compiler Engineer in Tel Aviv, you’ll lead the development of cutting-edge compiler technologies, optimize large-scale ML workloads, and bring new hardware to life. You’ll have the opportunity to influence architecture, mentor other engineers, collaborate with AWS services teams, and work on projects that span the full product lifecycle – from pre-silicon design to production.
A background in ML, compilers, or AI accelerators is a plus – but above all, we're looking for passionate engineers eager to innovate at scale.
A day in the life
As a Sr. Machine Learning Compiler Engineer on the AWS Neuron team, you will be a thought leader supporting the ground-up development and scaling of a compiler to handle the world's largest ML workloads. Architecting and implementing business-critical features, publish cutting-edge research, and mentoring a brilliant team of experienced engineers excites and challenges you. You will leverage your technical communications skill as a hands-on partner to AWS ML services teams and you will be involved in pre-silicon design, bringing new products/features to market, and many other exciting projects. A background in Machine Learning and AI accelerators is preferred, but not required.
About The Team
Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Utility Computing (UC)
AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll 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.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Basic Qualifications
- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience as a mentor, tech lead or leading an engineering team
Preferred Qualifications
- Bachelor's degree in computer science or equivalent
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, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Company - Annapurna Labs Ltd.
Job ID: A3034479