Amazon Web Services (AWS)
Software Engineering Manager, ML Kernel Performance, AWS Neuron, Annapurna Labs
Amazon Web Services (AWS), Cupertino, California, United States, 95014
Software Engineering Manager, ML Kernel Performance, AWS Neuron, Annapurna Labs
Join the Annapurna Labs team at Amazon Web Services (AWS) to accelerate deep learning and GenAI workloads on the Inferentia and Trainium ML accelerators. We build the AWS Neuron SDK and optimize its performance at the kernel level. The Acceleration Kernel Library team works at the forefront of maximizing performance for AWS’s custom ML accelerators. Working at the hardware‑software boundary, our engineers craft high‑performance kernels for ML functions, ensuring every FLOP counts in delivering optimal performance for our customers’ demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what’s possible in AI acceleration. The AWS Neuron SDK, developed by the Annapurna Labs team at AWS, is the backbone for accelerating deep learning and GenAI workloads on Amazon’s Inferentia and Trainium ML accelerators. This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch, enabling unparalleled ML inference and training performance. As part of the broader Neuron Compiler organization, our team works across multiple technology layers—from frameworks and compilers to runtime and collectives. We not only optimize current performance but also contribute to future architecture designs, working closely with customers to enable their models and ensure optimal performance. This role offers a unique opportunity to work at the intersection of machine learning, high‑performance computing, and distributed architectures. Key Responsibilities
Design and implement high‑performance compute kernels for ML operations, leveraging the Neuron architecture and programming models. Analyze and optimize kernel‑level performance across multiple generations of Neuron hardware. Conduct detailed performance analysis using profiling tools to identify and resolve bottlenecks. Implement compiler optimizations such as fusion, sharding, tiling, and scheduling. Work directly with customers to enable and optimize their ML models on AWS accelerators. Collaborate across teams to develop innovative kernel optimization techniques. A Day in the Life
As a Software Engineering Manager, you’ll design and code solutions to help our team drive efficiencies in software architecture. You’ll create metrics, implement automation, and resolve root causes of software defects. You’ll also build high‑impact solutions for our large customer base, participate in design discussions, code review, and communicate with internal and external stakeholders. Work cross‑functionally to help drive business decisions with your technical input, and operate in a startup‑like development environment where you focus on the most important stuff. About the Team
We operate in spaces that are very large, yet our teams remain small and agile. There is no blueprint—we’re inventing, experimenting, and learning. The team works closely with customers on their model enablement, providing direct support and optimization expertise to ensure their ML workloads achieve optimal performance on AWS ML accelerators. Basic Qualifications
3+ years of engineering team management experience. 7+ years of experience working directly within engineering teams. 3+ years of designing or architecting new and existing systems (design patterns, reliability, and scaling). 8+ years of leading the definition and development of multi‑tier web services. Knowledge of engineering practices and patterns for the full software/hardware/network development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations. Experience partnering with product or program management teams. Preferred Qualifications
Experience communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy. Experience recruiting, hiring, mentoring/coaching, and managing teams of Software Engineers to improve their skills and make them more effective. Amazon is an equal‑opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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Join the Annapurna Labs team at Amazon Web Services (AWS) to accelerate deep learning and GenAI workloads on the Inferentia and Trainium ML accelerators. We build the AWS Neuron SDK and optimize its performance at the kernel level. The Acceleration Kernel Library team works at the forefront of maximizing performance for AWS’s custom ML accelerators. Working at the hardware‑software boundary, our engineers craft high‑performance kernels for ML functions, ensuring every FLOP counts in delivering optimal performance for our customers’ demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what’s possible in AI acceleration. The AWS Neuron SDK, developed by the Annapurna Labs team at AWS, is the backbone for accelerating deep learning and GenAI workloads on Amazon’s Inferentia and Trainium ML accelerators. This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch, enabling unparalleled ML inference and training performance. As part of the broader Neuron Compiler organization, our team works across multiple technology layers—from frameworks and compilers to runtime and collectives. We not only optimize current performance but also contribute to future architecture designs, working closely with customers to enable their models and ensure optimal performance. This role offers a unique opportunity to work at the intersection of machine learning, high‑performance computing, and distributed architectures. Key Responsibilities
Design and implement high‑performance compute kernels for ML operations, leveraging the Neuron architecture and programming models. Analyze and optimize kernel‑level performance across multiple generations of Neuron hardware. Conduct detailed performance analysis using profiling tools to identify and resolve bottlenecks. Implement compiler optimizations such as fusion, sharding, tiling, and scheduling. Work directly with customers to enable and optimize their ML models on AWS accelerators. Collaborate across teams to develop innovative kernel optimization techniques. A Day in the Life
As a Software Engineering Manager, you’ll design and code solutions to help our team drive efficiencies in software architecture. You’ll create metrics, implement automation, and resolve root causes of software defects. You’ll also build high‑impact solutions for our large customer base, participate in design discussions, code review, and communicate with internal and external stakeholders. Work cross‑functionally to help drive business decisions with your technical input, and operate in a startup‑like development environment where you focus on the most important stuff. About the Team
We operate in spaces that are very large, yet our teams remain small and agile. There is no blueprint—we’re inventing, experimenting, and learning. The team works closely with customers on their model enablement, providing direct support and optimization expertise to ensure their ML workloads achieve optimal performance on AWS ML accelerators. Basic Qualifications
3+ years of engineering team management experience. 7+ years of experience working directly within engineering teams. 3+ years of designing or architecting new and existing systems (design patterns, reliability, and scaling). 8+ years of leading the definition and development of multi‑tier web services. Knowledge of engineering practices and patterns for the full software/hardware/network development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations. Experience partnering with product or program management teams. Preferred Qualifications
Experience communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy. Experience recruiting, hiring, mentoring/coaching, and managing teams of Software Engineers to improve their skills and make them more effective. Amazon is an equal‑opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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