Neuromorphic Applications Engineer (AI)

TL;DR

Neuromorphic Applications Engineer (AI): Developing and benchmarking advanced AI algorithms for hirify.global's next-generation neuromorphic hardware with an accent on edge computing, robotics, and physical AI systems. Focus on optimizing AI models for event-based architectures, validating SDKs, and translating experimental research into production-ready insights.

Location: Must be based in Guadalajara, Mexico (Hybrid work model).

Company

hirify.global is a global technology leader focused on creating world-changing technology that improves the lives of every person on Earth, from cloud computing to the Internet of Things.

What you will do

• Develop and optimize advanced AI algorithms and robotics applications for neuromorphic platforms.
• Evaluate and benchmark robotic workloads, such as VLA models for drones and humanoids.
• Validate the neuromorphic SDK by running real-world workloads and gathering performance metrics.
• Propose targeted software enhancements to the core development team.
• Present findings and publish benchmark results in top-tier conferences and journals.

Requirements

• Must have unrestricted, permanent right to work in Mexico (no visa sponsorship).
• Advanced English level required (resume must be submitted in English).
• MSc or PhD in Computer Science, Computer Engineering, Electrical Engineering, Robotics, Physics, or related field.
• 3+ years of experience writing clean, efficient, and modular Python and C++ code.
• 2+ years of experience with deep learning, mathematical optimization, and AI frameworks (PyTorch, JAX, TensorFlow).
• 1+ year of experience developing AI models for perception, reasoning, and control.

Culture & Benefits

• Fixed-term opportunity lasting approximately 12 months.
• Hybrid work model allowing for a mix of on-site and off-site work.
• Opportunity to work within hirify.global's CTO Office on cutting-edge neuromorphic technology.
• Access to professional development programs and semiconductor development courses.
• Collaborative environment with a global ecosystem of research groups.