AI Application Team Lead

NextSilicon is reimagining high-performance computing (HPC & AI). Our accelerated compute solutions leverage intelligent adaptive algorithms to vastly accelerate supercomputers, driving them forward into a new generation. We have developed a novel software-defined hardware architecture that is achieving significant advancements in both the HPC and AI domains.

At NextSilicon, everything we do is guided by three core values:

• Professionalism: We strive for exceptional results through professionalism and unwavering dedication to quality and performance.
• Unity: Collaboration is key to success. That's why we foster a work environment where every employee can feel valued and heard.
• Impact: We're passionate about developing technologies that make a meaningful impact on industries, communities, and individuals worldwide.
• impact on industries, communities, and individuals worldwide.
  
  

• 5+ years of experience in AI/ML engineering, performance optimization, or ML systems.
• Deep understanding of LLM architectures, training & inference mechanics, and modern ML frameworks.
• Strong proficiency in PyTorch ecosystem, with a specific focus on performance tuning via Triton, Cuda or MLIR-based compiler frameworks.
• Hands-on expertise profiling and optimizing kernels (GEMM, attention, softmax, token pipelines).
• Demonstrated experience running or tuning MLPerf or similar large-scale benchmarks.
• Strong Python and C++ development skills.
• Proven leadership experience: mentoring, guiding, or managing engineers.
  
  

• Lead and mentor a team of AI application and performance engineers.
• Run and optimize AI workloads (LLaMA, DeepSeek, etc.) and execute MLPerf benchmarks.
• Analyze end-to-end performance and identify HW/SW bottlenecks.
• Develop optimization strategies across models, kernels, frameworks, and runtime.
• Build profiling, debugging, and validation tools for large-scale AI workloads.
• Collaborate with hardware, compiler, and device software teams to improve performance.