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range of industries within the field of technology
At European Recruitment, our sectors cover a wide
range of industries within the field of technology
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Senior AI Software Engineer
Senior AI Software Engineer
Key Responsibilities
- AI Optimization and Co-design:
- Develop compile-time and run-time optimizations to enhance real-time AI applications.
- Innovate through the integration of application algorithms, frameworks, runtime environments, modeling, and simulation, influencing end-to-end architecture for AI processors.
- Technical Roadmap Development:
- Identify core technologies related to Neural Processing Unit (NPU) chips and outline evolutionary strategies to establish competitive technical advantages in the AI industry.
- AI Architecture Insights:
- Track AI trends and algorithm developments, defining key architecture solutions for usability and performance improvements across AI’s software and hardware stacks.
- Cross-functional Collaboration:
- Work alongside various teams to deploy solutions, ensuring high performance and robust functionality.
- Industry Engagement:
- Maintain an understanding of industry-leading architectures and mainstream models, aligning offerings with emerging applications.Person Specification
Required Skills:
- Expertise in AI Chips and Systems:
- Experience optimizing chip architectures with heterogeneous computing.
- Technical Proficiency:
- Numerical calculations, compilation, chip-algorithm co-design, runtime optimization, shared memory systems.
- Performance Analysis:
- Familiarity with performance sensitivities of micro-architecture features, compute/memory configurations, and AI acceleration strategies.
- Software & Framework Expertise:
- GPU/NPU-optimized libraries; hands-on with CUDA, OpenCL, or similar frameworks.
- Strong background in compiler optimizations (LLVM-MLIR experience desirable).
- Proficiency in C++, Python, and modern system development.
- Deep Learning Knowledge:
- Development experience with deep learning frameworks and deployment models.
Desired Skills:- Work across AI application domains such as modeling, inference frameworks (e.g., ONNXRuntime, IREE, TVM).
- Familiarity with industry tools and methods from leading AI tech providers.
- Commercializing AI Research:
- Experience bridging research and practical applications in commercialized solutions.
- Additional GPU Proficiency:
- Experience with AMD/NVIDIA GPUs and inference backend development.
- Deployment Familiarity:
- Hands-on deployment experience with AI models in real-world production environments.
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