HPC Performance Engineer for AI Training & Inference

CuspAI; Town of Cambridge; Hybrid; AUD 171,000 - 247,000; Full time

Benefits offered by this job

Competitive salary

Equity in CuspAI

Holiday allowance (DE/NL/UK: 28 days;

Parental leave: 26 weeks primary / 12,

Professional development budget

Meaningful problems tackling climate/S

Interdisciplinary teamwork

Job summary

CuspAI is seeking a Performance Engineer to bridge frontier AI models and high‑performance compute. You will optimize training/inference, profile workloads, and design scalable kernels to empower faster materials discovery.

Join a fast‑moving startup bridging AI research, chemistry, and engineering. You’ll collaborate with researchers and infrastructure to shape future compute clusters across Europe and beyond.

Qualifications

• 3+ years of experience in performance engineering, site reliability engineering, or low‑level software development, focused on HPC or AI workloads.
• Expert‑level knowledge of GPU architecture and CUDA kernel optimization; Triton experience.
• Strong understanding of distributed training frameworks (PyTorch Distributed, DeepSpeed, Megatron‑LM) and networking protocols.
• Proficiency in profiling tools such as Nsight Systems, Nsight Compute, or Weights & Biases for performance tracking.
• Builder mindset; able to work autonomously in a fast‑paced startup environment.

Responsibilities

• Training and inference optimization: map operations to hardware, focusing on NVIDIA kernels and NCCL.
• Profiling, observability and cost management: build real‑time dashboards tracking MFU, memory bandwidth, and cluster uptime.
• Interdisciplinary collaboration: work with AI researchers and infrastructure to optimize architectures and compute clusters.

Skills

Performance engineering

GPU architecture

Distributed training

Profiling tools

Autonomous startup mindset

Job description

CuspAI is seeking a Performance Engineer to bridge frontier AI models and high‑performance compute. You will optimize training/inference, profile workloads, and design scalable kernels to empower faster materials discovery.

Join a fast‑moving startup bridging AI research, chemistry, and engineering. You’ll collaborate with researchers and infrastructure to shape future compute clusters across Europe and beyond.