Senior Machine Learning Compiler Engineer

The Product: Join us in shaping the future of cloud innovation with AWS Machine Learning accelerators, which power cutting-edge Generative AI applications on AWS. Our custom silicon, like the Inferentia chip for ML inference and the Trainium chip for ML training, provides exceptional performance and cost efficiency at scale. Built on the AWS Neuron Software Development Kit (SDK), our technology features a deep learning compiler, a runtime, and seamless integration with popular ML frameworks such as PyTorch, TensorFlow, and MXNet. Major customers such as Snap, Autodesk, Amazon Alexa, and Amazon Rekognition are already experiencing the benefits of our technology. The Opportunity: We are expanding the AWS Neuron team, creating a unique chance for you to be part of the pioneering group, influencing our local culture and technical direction while contributing to a global mission. The team will play a critical role in developing the Neuron compiler stack—transforming high-level neural network models into high-performance execution on AWS custom hardware. The Team: As a part of Amazon Annapurna Labs, the AWS Neuron team integrates software, hardware, and silicon engineering. We collaborate closely with AWS service teams, directly enhancing the performance and scalability of ML workloads across the cloud. Our focus is on developing a powerful, high-performance toolchain that drives innovation in Generative AI. You: As a Senior Machine Learning Compiler Engineer, you will take the lead in developing cutting-edge compiler technologies, optimizing extensive ML workloads, and launching new hardware. This role offers you the chance to shape architecture, mentor fellow engineers, collaborate with AWS service teams, and engage in various projects that encompass the complete product lifecycle—from pre-silicon design to production. We seek passionate engineers ready to innovate at scale. A Day in the Life: In this role, you will be a thought leader in developing and scaling a compiler to support the world’s largest ML workloads. You will architect and implement critical features, contribute to cutting-edge research, and mentor a talented team. Your effective communication skills will be vital as you partner with AWS ML services teams, participating in pre-silicon design and bringing new products/features to market, among other exciting endeavors. About AWS: Amazon Web Services (AWS) stands as the world's most comprehensive and broadly adopted cloud platform. We lead in cloud computing innovation, providing trusted products and services for businesses ranging from startups to Global 500 companies. Our Utility Computing (UC) organization develops and manages a variety of services in AWS, including specialized solutions for customers requiring advanced security. Inclusive Team Culture: At AWS, we embrace learning and curiosity. Employee-led affinity groups cultivate an inclusive culture, promoting pride in our diversity. We host ongoing events and learning experiences aimed at celebrating uniqueness. Work/Life Balance: We prioritize work-life harmony, ensuring that success at work does not come at the expense of home life. Flexibility is vital to our working culture, empowering our employees to achieve greatness. Mentorship and Career Growth: We are committed to raising our performance bar, striving to become Earth's Best Employer. At AWS, you will find abundant opportunities for knowledge-sharing, mentorship, and resources for professional growth. Diverse Experiences: Amazon values the richness of diverse experiences. We encourage candidates from various backgrounds to apply, even if your experiences differ from the traditional career path. BASIC QUALIFICATIONS 5+ years of non-internship professional software development experience 5+ years of programming experience in at least one software language 5+ years of experience in leading design or architecture for new and existing systems 5+ years of full software development lifecycle experience, including coding standards, code reviews, source control management, build processes, testing, and operations Experience mentoring, leading tech initiatives, or managing an engineering team PREFERRED QUALIFICATIONS Bachelor's degree in computer science or equivalent We are an equal opportunity employer and do not discriminate based on protected veteran status, disability, or other legally protected statuses.