Amazon.com Services LLC
Technology
SoftwareDevMgr,MLCompiler,EdgeAIPlatform
Neural analysis suggests this role is
optimal for Manager candidates.
“Software Dev Mgr, ML Compiler, Edge AI Platform at Amazon.com Services LLC. Skills: ML Compiler, Edge AI, Deep learning, Compiler infrastructure. Lead and manage software engineers. Develop compiler infrastructure”
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
3+ years engineering team management, 7+ years working directly within engineering teams, 3+ years designing or architecting systems, Knowledge of engineering practices for full SDLC, Experience partnering with product management, Experience partnering with program management, Experience with neural network inference offload
Nice to Have
Experience communicating with users, Experience communicating with technical teams, Experience communicating with senior leadership, Experience recruiting and hiring engineers, Experience mentoring/coaching engineers, Experience managing teams of Software Engineers, 7+ years full software development life cycle, Experience with Machine Learning toolkits, Experience with Deep Learning toolkits, Experience building compiler development teams, Experience leading compiler development teams, Experience managing teams on accelerators, Experience managing teams on custom instruction sets
What You'll Do.
Lead and manage software engineers
Develop compiler infrastructure
Drive technical vision
Drive technical strategy
Manage project planning
Manage project execution
Manage project delivery
Deliver compiler solutions
Maintain partnerships
Drive hiring initiatives
Drive team building initiatives
Architect software stack
Oversee development software stack
Lead documentation efforts
Ensure successful delivery
Offload deep learning workloads
How You'll Work.
Team & Collaboration
Partner science teams; Hardware teams; Software teams; Applied science teams; Product teams
Communication Scope
Technical designs; Product strategy
Process & Methodology
Project planning, Project execution, Project delivery
Full Job Description
Come join us to accelerate deep learning networks on Az1/Az2/Az3 Neural Edge processors and beyond. We deliver solutions to offload Speech, Computer Vision and Generative AI workloads on a range of devices from Blink Smart Home camera to Echo Show line of products. We are looking for a talented and passionate engineering leader to manage an exciting technology creation team at Amazon. You will have an enormous opportunity to lead a team that makes a large impact on the design, architecture, and implementation of deep learning technologies embedded into consumer products used every day, by people you know. The position provides a unique opportunity to guide your team's contributions and make an impact from hardware design stage followed by pre and post silicon development as well as productizing it on consumer devices, while supporting both current and future compiler and ML accelerator architectures. In this role you will lead a team working alongside partner science teams to develop the compiler infrastructure and lower deep learning workloads to heterogeneous device backends. You will also drive partnerships with peer science teams to innovate on model quantization and compression techniques for efficient execution on hardware, ensuring scalability across current and future generations of ML accelerator architectures. Key job responsibilities Lead and manage a team of software engineers developing compiler infrastructure for deep learning accelerators · Drive technical vision and strategy for the deep learning compiler stack ·. Manage project planning, execution, and delivery of compiler solutions · Build and maintain strong partnerships with hardware, software, applied science and product teams ·. Develop and mentor team members, manage performance, and drive career growth · Drive hiring and team building initiatives · Architect and oversee development of software stack for deep learning accelerator · Lead design reviews, API development, and documentation effort
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