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Perception Deployment Engineer - Model Deployment & Optimization

Zoox· Software – Autonomy Software
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Hybrid (Foster City, CA / Boston, MA / Seattle, WA / San Diego, CA)$199k - $270kFull-timePosted 2w ago

About the role

Role focused on bringing production-ready, large-scale models to on-vehicle stacks through compression, acceleration, and edge deployment optimization using CUDA kernels and real-time inference for power- and thermal-constrained SOCs.

Responsibilities

  • Design and develop production-level, low latency, and memory-safe C++ and CUDA code for real-time perception algorithms on vehicle systems.
  • Optimize large-scale models (Multi-Modal Sensor Fusion models, LLMs, VLMs) using quantization (PTQ, QAT), pruning, and mixed-precision inference frameworks.
  • Architect and implement model conversion and compilation pipelines using TensorRT for edge deployment.
  • Perform parity checking, accuracy recovery, and latency benchmarking between PyTorch and compiled edge binaries.
  • Develop and optimize custom ML OPs and TensorRT Plugins with efficient CUDA kernels to minimize latency and maximize memory bandwidth on AI accelerators.

Qualifications

  • Production-level C++ (14/17/20) and Python programming skills, with experience in concurrent, memory-safe, real-time inference code for edge devices.
  • Deep expertise in model compression technologies (PTQ, QAT) and mixed-precision inference frameworks (INT8, FP8, BF16/FP16).
  • Proven experience optimizing large-scale models (Multi-Modal Sensor Fusion models, LLMs, VLMs/VLAs) with Efficient Attention mechanisms (FlashAttention, Linear Attention) and KV-cache optimization (PagedAttention).
  • Extensive experience with model conversion/compilation pipelines (ONNX, TensorRT, torch.compile) and latency benchmarking and model quality parity valuation.
  • Proficiency in low-level programming for AI accelerators, including developing and optimizing custom ML OPs and TensorRT Plugins with CUDA kernels.

Skills

Required:C++PythonModel compressionCUDATensorRTLow-level AI accelerator programming
Nice to have:ONNX

Benefits

  • paid time off (sick leave, vacation, bereavement)
  • unpaid time off
  • Zoox Stock Appreciation Rights
  • Amazon RSUs
  • health insurance
  • long-term care insurance
  • long-term and short-term disability insurance
  • life insurance
Last updated Oct 21, 2026. Interested? Apply on the company site.
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