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Member of Technical Staff, Inference

Reactor· Engineering
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Hybrid (San Francisco)Full TimePosted 5mo ago

About the role

ML Inference Engineer focused on high-performance inference for real-time world models, optimizing ultra-low-latency, high-throughput deployment across the inference stack.

Responsibilities

  • Drive our frontier position on model performance for diffusion models
  • Design and implement a high-performance in-house inference runtime
  • Implement optimizations using torch.compile, custom CUDA kernels, and specialized inference frameworks
  • Optimize neural network models through quantization, pruning, and architectural modifications
  • Profile and benchmark model performance to identify computational bottlenecks
  • Collaborate directly with model partner teams to integrate their models into our platform

Qualifications

  • Bachelor's degree in Computer Science, Electrical Engineering, or a related technical field (or equivalent practical experience)
  • Strong foundation in systems programming, with a track record of identifying and resolving bottlenecks
  • Deep expertise in PyTorch, TensorRT, TransformerEngine, Nsight, ONNX Runtime
  • Model compilation, quantization (INT8/FP16), and advanced serving architectures
  • Working knowledge of GPU hardware (NVIDIA)
  • Strong understanding of transformer architectures and modern ML optimization techniques

Skills

Required:model performance optimizationinference runtime developmenttorch.compileCUDAquantizationprofiling and benchmarkingcollaboration with model partners

Benefits

  • Competitive SF salary and meaningful early equity
  • Visa sponsorship and relocation support
  • Generous health, dental, and vision coverage
Last updated Oct 15, 2026. Interested? Apply on the company site.

About Reactor

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