Senior AI Software Engineer

Recruitment Consultant

Simon Troupe

Contact Details

[email protected] +44 (0)330 335 2369

Posted

7 days ago

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:

Broader AI Experience:
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.

Industry

Contract Type

Permanent

Location

United Kingdom

Work Model