AMD
Product Application Engineer - AI Models, AI Frameworks, Python, C++, Embedded S
AMD, San Jose, California, United States, 95199
Overview
Product Application Engineer - AI Models, AI Frameworks, Python, C++, Embedded Systems at AMD. This role focuses on owning and managing the customer experience for AMD’s Software Solutions for ML inferencing. The Role
AMD is looking for a highly motivated product engineer to own and manage the customer experience for AMD’s Software Solutions for ML inferencing. The successful candidate will: Facilitate adoption of AMD’s ML inferencing solutions by onboarding customers and delivering best-in-class customer experience Work with R&D, marketing, and key customers to drive the evolution of the product Support strategic business engagements leveraging AMD’s ML inferencing solutions Key Responsibilities
Evaluate end-to-end ML inferencing pipelines optimized for AMD’s Embedded devices. This includes performance benchmarking, memory profiling, bottleneck analysis, and usability analysis for model inferencing flows. Develop use cases, examples, tutorials, and methodology collateral for AI inference software components and ecosystems, including Compiler, Quantizer, Optimizer, Runtime, Profiler, Visualizer, Debugger, and more for embedded devices. Collaborate with engineering teams to provide early feedback on product development, analyze product/feature specifications and usability, and identify customer pain points. Interact with internal and external customers to understand issues, assist with debugging workflows to meet model and flow requirements, and create use cases to reproduce issues to drive adoption. Collaborate with sales and marketing on strategic business engagements. Work with R&D to prioritize issues and manage escalations. Preferred Experience
Experience with AI/ML frameworks such as PyTorch and ONNX in resource-constrained embedded environments. Proven expertise deploying, optimizing, and troubleshooting ML models on embedded hardware platforms (microcontrollers, custom SoCs, FPGAs, etc.). Hands-on experience integrating AI/ML workloads with embedded RTOS or bare-metal environments, including firmware-level model execution. Understanding of embedded system constraints (compute, memory, power) and tailoring ML solutions accordingly. Experience with state-of-the-art models (CNNs, Transformers, LLMs, Generative AI) as run or adapted for embedded platforms. Skills in ML model analysis, performance benchmarking, bottleneck analysis, and accuracy testing on embedded devices. Experience quantizing, pruning, and compressing ML networks for efficient deployment on embedded/edge devices. Experience in hardware/software co-design, collaborating with embedded systems engineers to optimize end-to-end ML inference pipelines. Proficiency in programming languages and tools relevant for embedded and AI development (e.g., Python, C, C++, cross-compilation toolchains, debugging tools like JTAG/SWD). Familiarity with development/build tools such as Git, CMake, Make, Conda, Docker, VSCode, Bash, Linux, and embedded platforms/tools. Strong technical documentation skills to present solutions and methodologies to stakeholders at all levels. Excellent analytical, problem-solving, and communication skills, with experience collaborating across hardware, software, and customer-facing teams. Academic Credentials
Bachelor’s or Master’s in computer engineering, computer science, electrical engineering, or comparable disciplines. Location
San Jose, CA Longmont, CO Benefits offered are described: AMD benefits at a glance. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
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Product Application Engineer - AI Models, AI Frameworks, Python, C++, Embedded Systems at AMD. This role focuses on owning and managing the customer experience for AMD’s Software Solutions for ML inferencing. The Role
AMD is looking for a highly motivated product engineer to own and manage the customer experience for AMD’s Software Solutions for ML inferencing. The successful candidate will: Facilitate adoption of AMD’s ML inferencing solutions by onboarding customers and delivering best-in-class customer experience Work with R&D, marketing, and key customers to drive the evolution of the product Support strategic business engagements leveraging AMD’s ML inferencing solutions Key Responsibilities
Evaluate end-to-end ML inferencing pipelines optimized for AMD’s Embedded devices. This includes performance benchmarking, memory profiling, bottleneck analysis, and usability analysis for model inferencing flows. Develop use cases, examples, tutorials, and methodology collateral for AI inference software components and ecosystems, including Compiler, Quantizer, Optimizer, Runtime, Profiler, Visualizer, Debugger, and more for embedded devices. Collaborate with engineering teams to provide early feedback on product development, analyze product/feature specifications and usability, and identify customer pain points. Interact with internal and external customers to understand issues, assist with debugging workflows to meet model and flow requirements, and create use cases to reproduce issues to drive adoption. Collaborate with sales and marketing on strategic business engagements. Work with R&D to prioritize issues and manage escalations. Preferred Experience
Experience with AI/ML frameworks such as PyTorch and ONNX in resource-constrained embedded environments. Proven expertise deploying, optimizing, and troubleshooting ML models on embedded hardware platforms (microcontrollers, custom SoCs, FPGAs, etc.). Hands-on experience integrating AI/ML workloads with embedded RTOS or bare-metal environments, including firmware-level model execution. Understanding of embedded system constraints (compute, memory, power) and tailoring ML solutions accordingly. Experience with state-of-the-art models (CNNs, Transformers, LLMs, Generative AI) as run or adapted for embedded platforms. Skills in ML model analysis, performance benchmarking, bottleneck analysis, and accuracy testing on embedded devices. Experience quantizing, pruning, and compressing ML networks for efficient deployment on embedded/edge devices. Experience in hardware/software co-design, collaborating with embedded systems engineers to optimize end-to-end ML inference pipelines. Proficiency in programming languages and tools relevant for embedded and AI development (e.g., Python, C, C++, cross-compilation toolchains, debugging tools like JTAG/SWD). Familiarity with development/build tools such as Git, CMake, Make, Conda, Docker, VSCode, Bash, Linux, and embedded platforms/tools. Strong technical documentation skills to present solutions and methodologies to stakeholders at all levels. Excellent analytical, problem-solving, and communication skills, with experience collaborating across hardware, software, and customer-facing teams. Academic Credentials
Bachelor’s or Master’s in computer engineering, computer science, electrical engineering, or comparable disciplines. Location
San Jose, CA Longmont, CO Benefits offered are described: AMD benefits at a glance. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
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