Neuromorphic AI Research Scientist — Edge AI Innovator

Intel; Austin (TX); Hybrid; USD 171,000 - 315,000; Full time

Benefits offered by this job

Stock bonuses

Health benefits

Vacation

Job summary

Intel’s Neuromorphic Computing Lab seeks a Neuromorphic AI Research Scientist to advance processor technology toward commercial adoption. You will design, prototype, and evaluate algorithms for edge computing, signal processing, and autonomous systems, while collaborating with cross-disciplinary teams.

Requirements include a PhD or equivalent, 1+ prototypes with rigorous evaluation, and 3+ publications in AI/ML or related areas.

Qualifications

• PhD (or equivalent) in Computational Neuroscience, Computer Science, Electrical Engineering, Applied Mathematics, Robotics, or related field.
• 1+ projects turning research ideas into prototypes with rigorous evaluation.
• 3+ publications in AI/ML, edge computing, robotics or control.

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.
• Prototype and evaluate approaches under quantization, sparsity, memory footprint, latency, and energy constraints.
• Collaborate with hardware & software teams to translate requirements into hardware specs.
• Build experimental pipelines and benchmarks with baselines and ablations.
• Communicate results via documentation, customer prototypes, and publications.

Skills

Innovative problem-solving

Collaborative leadership

Adaptability

Communication excellence

Results-oriented

Intellectual curiosity

Education

PhD in Computational Neuroscience / CS / EE

Tools

Python

C/C++

Job description

Intel’s Neuromorphic Computing Lab seeks a Neuromorphic AI Research Scientist to advance processor technology toward commercial adoption. You will design, prototype, and evaluate algorithms for edge computing, signal processing, and autonomous systems, while collaborating with cross-disciplinary teams.

Requirements include a PhD or equivalent, 1+ prototypes with rigorous evaluation, and 3+ publications in AI/ML or related areas.