Sr. Product Development Engineer - AI/ML Frameworks, Python

About the Role

Key Responsibilities

• Evaluate end-to-end ML inferencing pipelines optimized for AMD's Embedded devices, including performance benchmarking, memory profiling, and bottleneck analysis.
• Develop use cases, examples, tutorials, and methodology collaterals for AI inference software components and ecosystems, including Compiler, Quantizer, Optimizer, Runtime, Profiler, Visualizer, Debugger, and more targeting embedded devices.
• Engage with engineering teams to collaborate on product development, analyze product/feature specifications and usability to provide early feedback, and understand product/feature usage holistically to identify potential customer pain points.
• Interact with internal and external customers to understand their issues, assist them in debugging workflows to meet model and flow-specific requirements, and create use cases to reproduce issues, driving successful adoption.
• Collaborate with sales and marketing teams on strategic business engagements.
• Work closely with R&D to prioritize issues and manage escalations.

Requirements

• Experience working with AI frameworks such as PyTorch and ONNX.
• Proven experience deploying and optimizing ML models on embedded hardware (microcontrollers, custom SOCs or similar platforms).
• Hands-on experience with Python, C, and C++.
• Expertise with development tools such as Git, CMake, Make, Conda, Docker, VSCode, bash, Linux.
• Demonstrated expertise in performance analysis and debugging across software/hardware boundaries.
• Bachelor's or Master's in computer engineering, computer science, electrical engineering, or comparable disciplines.
• Excellent analytical, problem-solving, and communication skills.
• Ability to think from the end-user's perspective, understand their needs, and advocate for them.

Nice to Have

• Experience working with AI frameworks such as PyTorch and ONNX.
• Work experience with state-of-the-art models in domains like CNN, Transformers, LLMs, Generative AIs.
• Experience in model analysis (CNN, LLM), performance, benchmarking, and accuracy testing.
• Experience in quantizing and pruning ML networks.
• Experience working on and managing open-source AI projects.

Qualifications

• Bachelor's or Master's in computer engineering, computer science, electrical engineering, or comparable disciplines.

Benefits & Perks

• Competitive benefit packages and an award-winning culture.