Amazon Web Services (AWS)
SDE I - Systems, Runtime, and ML Infrastructure (AWS Custom Silicon), Annapurna
Amazon Web Services (AWS), Seattle, Washington, us, 98127
SDE I - Systems, Runtime, and ML Infrastructure (AWS Custom Silicon), Annapurna Labs
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SDE I - Systems, Runtime, and ML Infrastructure (AWS Custom Silicon), Annapurna Labs
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Amazon Web Services (AWS) Description At AWS, we're pioneering the future of cloud computing and AI acceleration through innovative hardware-software co-design. Our teams within Annapurna Labs and AWS AI are creating the foundation for next-generation cloud infrastructure that powers thousands of customers worldwide, from startups to global enterprises. We operate at an unprecedented scale, designing custom silicon chips, advanced networking solutions, and ML accelerators. Our work spans from hardware abstraction to high-performance distributed training systems, offering early-career engineers opportunities to make impactful contributions. Key job responsibilities
Develop and optimize software for custom hardware and ML infrastructure Collaborate with hardware teams to understand chip architecture Implement and improve networking, runtime, and system software Build and maintain profiling, monitoring, and debugging tools for ML workloads Contribute to open-source ML frameworks and infrastructure projects Participate in code reviews and follow best practices Learn and apply new technologies to solve engineering challenges About The Team
Applicants will be routed to specific teams based on interests and needs: The Elastic Network Adapter (ENA) team enhances EC2 networking capabilities. The AWS Neuron SDK team develops software for custom ML accelerators like Inferentia and Trainium. The Machine Learning Server Software team maintains high-performance ML servers. The SoC Hardware Abstraction Layer (HAL) team develops middleware for custom silicon chips. Qualifications
Basic: Bachelor’s or Master’s degree expected between Dec 2022 and Sep 2025 Strong programming skills in C/C++ or Python, with solid understanding of data structures and algorithms Knowledge of computer architecture, operating systems, Linux Internship or project experience in systems programming, networking, or ML Preferred: Familiarity with version control (e.g., Git) and development methodologies Knowledge of ML frameworks (e.g., PyTorch, TensorFlow) Interest in open-source contributions Amazon is an equal opportunity employer. For accommodations during the application process, visit https://amazon.jobs/content/en/how-we-hire/accommodations. The salary range varies by location, from $99,500 to $200,000 annually, with additional benefits and compensation options. This position remains open until filled. Apply via our careers site.
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Join to apply for the
SDE I - Systems, Runtime, and ML Infrastructure (AWS Custom Silicon), Annapurna Labs
role at
Amazon Web Services (AWS) Description At AWS, we're pioneering the future of cloud computing and AI acceleration through innovative hardware-software co-design. Our teams within Annapurna Labs and AWS AI are creating the foundation for next-generation cloud infrastructure that powers thousands of customers worldwide, from startups to global enterprises. We operate at an unprecedented scale, designing custom silicon chips, advanced networking solutions, and ML accelerators. Our work spans from hardware abstraction to high-performance distributed training systems, offering early-career engineers opportunities to make impactful contributions. Key job responsibilities
Develop and optimize software for custom hardware and ML infrastructure Collaborate with hardware teams to understand chip architecture Implement and improve networking, runtime, and system software Build and maintain profiling, monitoring, and debugging tools for ML workloads Contribute to open-source ML frameworks and infrastructure projects Participate in code reviews and follow best practices Learn and apply new technologies to solve engineering challenges About The Team
Applicants will be routed to specific teams based on interests and needs: The Elastic Network Adapter (ENA) team enhances EC2 networking capabilities. The AWS Neuron SDK team develops software for custom ML accelerators like Inferentia and Trainium. The Machine Learning Server Software team maintains high-performance ML servers. The SoC Hardware Abstraction Layer (HAL) team develops middleware for custom silicon chips. Qualifications
Basic: Bachelor’s or Master’s degree expected between Dec 2022 and Sep 2025 Strong programming skills in C/C++ or Python, with solid understanding of data structures and algorithms Knowledge of computer architecture, operating systems, Linux Internship or project experience in systems programming, networking, or ML Preferred: Familiarity with version control (e.g., Git) and development methodologies Knowledge of ML frameworks (e.g., PyTorch, TensorFlow) Interest in open-source contributions Amazon is an equal opportunity employer. For accommodations during the application process, visit https://amazon.jobs/content/en/how-we-hire/accommodations. The salary range varies by location, from $99,500 to $200,000 annually, with additional benefits and compensation options. This position remains open until filled. Apply via our careers site.
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