AI Research Scientist (Photonic & Neuromorphic Computing)

TL;DR

AI Research Scientist (Photonic & Neuromorphic Computing): Designing AI algorithms, architectures, and simulation frameworks for emerging non-traditional computing platforms with an accent on hardware-aware optimization and physics-based modeling. Focus on developing digital twins capturing physical effects, co-designing algorithms with hardware constraints, and benchmarking neuromorphic system performance.

Location: Open to remote within the US. Primary location: Boston, US

Company

Building verifiable, interpretable AI systems combining deep learning, formal logic, and physics-based modeling to accelerate semiconductor and photonic hardware development.

What you will do

• Develop simulation and digital-twin tools capturing physical effects like nonlinearities, noise, and precision limits for hardware-aware algorithm development.
• Collaborate with AI, software, and hardware teams to align algorithms with system constraints and automate scientific workflows.
• Design and prototype machine-learning architectures and physics-aware optimization for neuromorphic systems.
• Evaluate performance tradeoffs, conduct benchmarking studies, document results, and contribute to R&D decisions.

Requirements

• PhD in Computer Science, Artificial Intelligence, Physics, Electrical Engineering, Applied Mathematics, or related field.
• Strong background in machine learning and neural-network architectures, with experience or interest in hardware-algorithm co-design, neuromorphic, or unconventional computing.
• Expert-level proficiency in Python and modern ML frameworks.
• Solid understanding of scientific computing, modeling, and data-driven experimentation.
• Ability to collaborate in a multidisciplinary, fast-paced research environment.

Nice to have

• Background in photonic, analog, or non-CMOS computing systems.
• Experience with spiking neural networks, energy-efficient AI, or hardware-aware ML.
• Familiarity with physical simulation tools or custom modeling pipelines.
• Contributions to open-source or research software projects.

Culture & Benefits

• Competitive compensation and stock options plan.
• Access to cutting-edge tools and collaboration with AI, physics, and hardware experts.
• Professional growth through conferences, research presentations, and global AI community engagement.
• Impact-driven culture focused on challenging AI-hardware problems.