Senior / Principal Neuromorphic Systems Architect

Flagship Pioneering•Cambridge, MA

About The Position

The Company Flagship Labs 119 Inc. (FL119) is an early-stage technology company pioneering a new frontier at the intersection of neuroscience and computation. We are developing next-generation technologies to transform how intelligent systems are built. We believe that the future of artificial intelligence demands a fundamental rethinking of today’s paradigms. Our mission is bold and urgent: to build a future where naturalistic, robust intelligence can emerge and operate sustainably at scale. FL119 is backed by Flagship Pioneering, which brings the courage, long-term vision, and resources needed to realize unreasonable results. At FL119, we are uniquely cross-functional and collaborative. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way. The Role: FL119 is seeking a creative and deeply technical Neuromorphic Systems Architect to join our team. Leveling is flexible based on experience. This role will focus on translating nonlinear neural dynamics into next-generation computational architectures. You will work at the interface of neuroscience, dynamical systems theory, and hardware engineering to design and prototype electronic architectures that embody biologically derived principles of computation. This is not a conventional AI accelerator role. We are seeking someone who can rethink compute from first principles, designing architectures that leverage recurrence, nonlinearity, sparsity, event-driven signaling, and adaptive dynamics as foundational primitives rather than constraints.

Requirements

PhD (or equivalent experience) in Electrical Engineering, Applied Physics, Computational Neuroscience, Computer Engineering, or a closely related field.
Deep expertise in nonlinear dynamical systems and their application to computation.
Experience designing hardware architectures (ASIC, FPGA, analog/mixed-signal, or emerging device technologies such as RRAM, PCM, memristors, etc.).
Strong mathematical foundation in dynamical systems, control theory, or computational modeling.
Demonstrated ability to move from theory to implementable system design.
5+ years of relevant research or industry experience (level dependent)

Nice To Haves

Prior work in neuromorphic computing or spiking neural network hardware.
Experience with event-driven or asynchronous architectures.
Familiarity with reservoir computing, recurrent dynamical systems, or physical computing substrates.
Experience working in early-stage, fast-paced R&D environments.
Track record of patents or high-impact publications in neuromorphic systems or unconventional computing.

Responsibilities

Formalize brain-derived computation using dynamical systems theory and translate these insights into hardware-relevant abstractions.
Architect novel neuromorphic or neuro-inspired hardware systems (analog, mixed-signal, in-memory, or alternative substrates).
Define system-level architecture, including memory models, communication schemes, and energy-efficient compute primitives.
Collaborate with neuroscience, signal processing, and machine learning teams to ensure tight coupling between biological insight and architectural design.
Lead feasibility studies, simulations, and early-stage prototyping efforts.
Evaluate trade-offs across CMOS, emerging devices, photonic, memristive, or other unconventional compute substrates.
Contribute to IP strategy, including invention disclosures and patents.
Help shape the long-term compute vision of the company.