Neuromorphic/AI Research Scientist

About the role

Intel's Neuromorphic Computing Lab has been at the forefront of brain-inspired computing for nearly a decade, working alongside a global ecosystem of 250+ research groups. Our groundbreaking Loihi series research chips have pioneered event-driven, sparse, and massively parallel neuro-inspired processing, resulting in over 100 peer-reviewed publications. As part of Intel's CTO Office, we're now transforming these research breakthroughs into real-world products that will power the next generation of physical AI systems. We are seeking a Neuromorphic AI Research Scientist to advance state-of-the-art neuromorphic processor technology toward commercial adoption. This role focuses on modeling, prototyping, and defining architectures and algorithms that enable transformative gains for real-world customer applications in edge computing, signal processing, and autonomous systems.

Responsibilities

• Design and analyze neuromorphic AI algorithms for robotics, signal processing, control, and learning on edge platforms
• Develop research-quality software artifacts including APIs, kernels, and benchmarking tools that enable collaborative innovation
• Prototype and evaluate approaches under realistic constraints including quantization, sparsity, memory footprint, latency, and energy optimization
• Collaborate with hardware and software engineering teams to translate algorithmic requirements into hardware specifications
• Build experimental pipelines and benchmarks for target use cases with comprehensive baseline and ablation studies
• Communicate results through technical documentation, customer prototypes, and publications in leading conferences and journals
• Contribute to technical thought leadership in neuromorphic computing and present findings to internal and external stakeholders

Skills

• Innovative Problem-Solving: Skills to approach complex challenges with creative, out-of-the-box thinking
• Collaborative Leadership: Strong interpersonal skills to work effectively across diverse, multidisciplinary teams
• Adaptability: Flexibility to navigate the dynamic landscape of emerging AI technologies
• Communication Excellence: Skills to articulate complex technical concepts to both technical and non-technical audiences
• Results-Oriented Mindset: Drive to translate research innovations into practical, commercial solutions
• Intellectual Curiosity: Passion for continuous learning and staying at the cutting edge of neuromorphic computing