Staff SW Systems Engineer (9291)
Job Summary
Job Description
Seeking a Senior/Staff/Principal Engineer with deep expertise in GPU/TPU acceleration for Edge AI. Must have extensive hands-on experience in local Large Language Model (LLM) inference and embedded GPU/TPU architectures. You'll play a crucial role in shaping future Edge AI solutions by developing and optimizing AI inference models for deployment on edge devices.
Must have:
- GPU/TPU Acceleration
- Edge AI Inference
- Large Language Models
- Embedded Architectures
Good to have:
- Micro-architecture Development
- Performance Profiling
- Edge Computing Platforms
- AI Frameworks
3 skills required
Job Details
Senior/Staff/Principal Engineer – Edge AI LLM 9291
We are seeking a talented Senior/Staff/Principal Engineer with specialized expertise in GPU/TPU acceleration to join our team. The ideal candidate will have extensive hands-on experience in local Large Language Models (LLM) inference with embedded GPU/TPU architectures. As Principal Engineer specializing in Edge AI, you will play a crucial role in shaping the future Edge AI solution, leveraging the power of GPU/TPU acceleration and enterprise grade, large scale edge compute.
The successful candidate will combine technical excellence with effective leadership, creating a positive impact on both projects and team dynamics.
Key Responsibilities:
- High-Level Design and Architecture
- Influence the Edge AI strategy by providing expert advice on design and architecture.
- Make critical decisions regarding technical directions, scalability, and system performance.
- Develop and optimize AI inference models for deployment on edge devices with embedded GPU/TPU accelerators, focusing on local Low Latency Model (LLM) inference.
- Implement and fine-tune low-latency model inference pipelines to meet real-time performance requirements.
- Collaborate with cross-functional teams to integrate AI inference solutions into edge computing platforms and applications.
- Collaborate with the GPU Hardware Design Team to design and optimize GPUs that power next-generation devices.
- Conduct performance profiling and optimization to maximize the efficiency of GPU/TPU acceleration for local LLM inference.
- Work on micro-architecture development, ensuring efficient execution of graphics, compute, and AI workloads within energy and area constraints.
- Stay current with advancements in GPU/TPU technologies and edge AI frameworks, incorporating them into solution designs as appropriate.
- Provide technical expertise and support to project teams, ensuring successful implementation and deployment of edge AI solutions.
Team Leadership:
- Lead and inspire a team of engineers, providing guidance, setting goals, and ensuring collaboration.
- Oversee project planning, execution, and delivery, ensuring alignment with business objectives.
- Manage all phases of technical projects, from conception to completion.
- Develop project specifications, track progress, and control costs.
- Foster a positive work environment, encouraging professional growth and knowledge sharing.
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