HiringCafe
Posted 5mo ago

AI Inference Engineer

@ Quadric
View All Jobs
Burlingame, California, United States
HybridFull Time
Responsibilities:port models, optimize inference, profile performance
Requirements Summary:Bachelor’s or Master’s in Computer Science or Electrical Engineering; 5+ years AI/LLM model inference; quantization and profiling experience; proficient in C/C++ and Python; familiarity with ONNX Runtime, PyTorch, vLLM, and related tools.
Technical Tools Mentioned:C/C++, Python, ONNX Runtime, PyTorch, vLLM, HuggingFace Transformers, Neural Compressor, llama.cpp
Save
Mark Applied
Hide Job
Report & Hide
Job Description

Quadric has created an innovative general purpose neural processing unit (GPNPU) architecture. Quadric's co-optimized software and hardware is targeted to run neural network (NN) inference workloads in a wide variety of edge and endpoint devices, ranging from battery operated smart-sensor systems to high-performance automotive or autonomous vehicle systems. Unlike other NPUs or neural network accelerators in the industry today that can only accelerate a portion of a machine learning graph, the Quadric GPNPU executes both NN graph code and conventional C++ DSP and control code.

Role

The AI Inference Engineer in Quadric is the key bridge between the world of AI/LLM models and Quadric unique platforms. The AI Inference Engineer at Quadric will [1] port AI models to Quadric platform; [2] optimize the model deployment for efficient inference; [3] profile and benchmark the model performance. This senior technical role demands deep knowledge of AI model algorithms, system architecture and AI toolchains/frameworks.

This California Bay Area based role follows a hybrid schedule, with at least two in-office days per week at our Burlingame office, the ability to commute regularly, and occasional additional onsite days as needed based on team and business priorities. The team and company also gather periodically for onsite meetings and offsite events, which are valued opportunities to connect, collaborate, and align.

Responsibilities

  • Quantize, prune and convert models for deployment
  • Port models to Quadric platform using Quadric toolchain
  • Optimize inference deployment for latency, speed
  • Benchmark and profile model performance and accuracy
  • Collaborate across related areas of the AI inference stack to support team and business priorities
  • Develop tools to scale and speed up the deployment
  • Make Improvement to SDK and runtime
  • Provide technical support and documents to customers and developer community