Senior AI Software Engineer (AI)

TL;DR

Senior AI Software Engineer (AI): Designing and optimizing model-zoo infrastructure for next-generation computer vision, generative AI, and LLM workloads with an accent on NPU accelerators. Focus on developing compilation, inference, and performance workflows, and building high-quality benchmarking pipelines and demos.

Location: Guadalajara, Mexico (Onsite)

Company

hirify.global is a global leader in secure connectivity solutions for embedded applications, focusing on innovation-driven work culture and cutting-edge AI hardware.

What you will do

• Scale and expand CNN and LLM/VLM model zoos using Python and C++.
• Improve model accuracy and re-implement variants in PyTorch for integration with optimization tools.
• Optimize, prune, and tune AI performance using the MCW tool for NPU accelerators.
• Develop gstreamer/nnstreamer plugins and end-to-end inference pipelines.
• Build and validate automated testing frameworks and Jenkins-based CI pipelines.
• Execute benchmarking and performance profiling for AI workloads, measuring latency, throughput, and power.

Requirements

• Bachelor’s degree in Electronics, Computer, Systems, or Robotics Engineering.
• 5+ years of experience in Machine Learning or related fields.
• Strong proficiency in Python and C/C++ for low-level performance and automation.
• Solid understanding of deep learning architectures across CV, NLP, and generative models.
• Experience with Hugging Face APIs and LLM benchmarking frameworks (MMLU, HumanEval, etc.).
• Fluency in English (written and spoken) is required.

Nice to have

• Experience with NPU architectures, compiler toolchains, and runtime environments.
• Proficiency with AI frameworks such as TensorFlow, PyTorch, Caffe, and ONNX pipelines.
• Experience in hardware/software performance evaluation and profiling.

Culture & Benefits

• Hands-on experience with next-generation AI accelerator hardware and NXP SDKs.
• Exposure to a diverse range of customer models across CV, LLM, VLM, and Generative AI domains.
• Inclusive, collaborative, and innovation-driven environment with the freedom to explore ideas.
• Deep exposure to end-to-end AI pipelines and benchmarking methodologies.