Senior/Staff Software Engineer (CUDA Expert)

Job Description

• Deep experience with GPU programming (CUDA, Triton, or OpenCL), with a focus on performance optimization for deep learning workloads.
• Strong understanding of large language model architectures (e.g., Transformer variants) and experience profiling and tuning their performance.
• Familiarity with memory management, kernel fusion, quantization, tensor parallelism, and GPU-accelerated inference.
• Experience with PyTorch internals or custom kernel development for AI workloads.
• Hands-on knowledge of low-level optimizations in training and inference pipelines, such as FlashAttention, fused ops, and mixed-precision computation.
• Proficiency in Python and C++
• Familiarity with inference acceleration frameworks like TensorRT, DeepSpeed, vLLM, or ONNX Runtime.

• Demonstrated experience profiling and debugging GPU performance bottlenecks in LLM training or inference pipelines.
• Has optimized large-scale ML workloads for throughput, latency, or cost—especially in production or research environments.
• Experience contributing to or implementing custom GPU kernels for high-impact components (e.g., attention, normalization, or activation layers).
• Proven ability to work across research and engineering teams to bridge model design and system performance.
• Has designed infrastructure that scales across hundreds or thousands of GPUs in cloud or on-prem clusters.

• High-Impact, Cross-Functional Work
• Cutting-Edge GPU & LLM Optimization
• Greenfield & Production-Scale Systems
• Ownership & Growth
• Engineering-Driven Culture
• Remote work, with quarterly trips to Sao Paulo
• Top Tier Medical Insurance
• Top Tier Dental and Vision Insurance
• 20 days time off, 14 company holidays
• Life Insurance and AD&D
• Extended maternity and paternity leaves
• 401K Saving Plans