Senior Software Engineer (AI Systems Performance)

A leading semiconductor and high-performance computing company is looking for a software engineer who is passionate about Distributed Inferencing on GPUs and improving the performance of key applications and benchmarks. You will be a member of a core team of incredibly talented industry specialists and will work with the very latest hardware and software technology

We are seeking a software engineer with strong technical expertise in C++/ Python development, solving performance and investigating scalability on multi-GPU, multi-node clusters. He is also passionate about quality assurance, benchmarking, and automation in the AI/ML space. The ideal candidate thrives in both collaborative and independent environments, demonstrates excellent problem-solving skills, and takes ownership in defining goals and delivering impactful solutions.

KEY RESPONSIBILITIES:

Distributed AI Enablement and Benchmarking: Enable and benchmark AI models on large-scale distributed systems to evaluate performance, accuracy, and scalability.

Scalable Systems Optimization: Optimize AI workloads across scale-up (multi-GPU), scale-out (multi-node), and scale-across distributed system configurations.

Cross-Team Collaboration: Collaborate closely with internal GPU library teams to analyze and optimize distributed workloads for high throughput and low latency.

Parallelization Strategies: Develop and apply optimal parallelization strategies for AI workloads to achieve best-in-class performance across diverse system configurations.

Model Infrastructure and Management: Contribute to distributed model management systems, model zoos, monitoring frameworks, benchmarking pipelines, and technical documentation.

Performance Monitoring and Visualization: Build and maintain real-time dashboards reporting performance, accuracy, and reliability metrics for internal stakeholders and external users.