Tech Lead, Functional Modeling

About Neurophos:

We are developing an ultra-high-performance, energy-efficient photonic AI inference system. We’re transforming AI computation with the first-ever metamaterial-based optical processing unit (OPU).

As AI adoption accelerates, data centers face significant power and scalability challenges. Traditional solutions are struggling to keep up, leading to rapidly rising energy consumption and costs. We’re solving both problems with an OPU that integrates over one million micron-scale optical processing components on a single chip. This architecture will deliver up to 100 times the energy efficiency of existing solutions while significantly improving large-scale AI inference performance.

We’ve assembled a world-class team of industry veterans and recently raised a $110M Series A led by Gates Frontier. Participants include M12 (Microsoft’s Venture Fund), Carbon Direct Capital, Aramco Ventures, Bosch Ventures, Tectonic Ventures, Space Capital, and others. We have also been recognized on the EE Times Silicon 100 list for several consecutive years.

Join us and shape the future of optical computing!

Location: San Francisco Bay Area or Austin, TX. Full-time onsite position.

Position Overview:

We are seeking an experienced Lead for Functional Modeling (FMOD) to establish and drive our functional modeling infrastructure, enabling early software development and RTL validation. This leadership role combines deep technical expertise in hardware functional modeling with team leadership responsibilities. You will build the FMOD team, define modeling methodologies using our YinYang event-driven framework, and create high-fidelity functional models of our novel optical computing platform that enable software teams to develop ahead of silicon.

Key Responsibilities:

• Lead the FMOD team (4+ engineers) focused on functional modeling and software enablement

• Architect and implement functional models of optical GEMM engines, SRAM vector processors, and dataflow engines

• Define functional modeling methodologies within the YinYang (libyy) event-driven framework

• Build transaction-level models (TLM) with clean interfaces between compute blocks

• Develop both execution-driven and trace-driven simulation capabilities

• Integrate SystemC/TLM 2.x models with custom C++ simulation infrastructure

• Enable early software development by providing high-performance functional simulators

• Collaborate with RTL teams on functional validation and co-simulation strategies

• Define modeling abstractions and component interfaces that enable team parallelism

• Mentor modeling engineers and establish team development practices

• Drive functional correctness validation through a comprehensive test infrastructure

Qualifications:

• MS or PhD in Computer Engineering, Electrical Engineering, or Computer Science (or BS with equivalent experience)

• 10+ years of experience in functional modeling, hardware emulation, or system-level simulation

• Proven experience building and leading technical teams (3+ years of management experience)

• Deep expertise in both execution-driven and trace-driven simulation methodologies

• Strong proficiency with SystemC and Transaction-Level Modeling (TLM 2.x)

• Expert-level C++ programming (C++17/20/23) with focus on modularity and performance

• Experience designing clean abstraction layers for complex hardware systems

• Track record of shipping functional models that enabled software development or RTL validation

• Excellent communication skills and ability to collaborate across hardware and software teams

• Understanding of computer architecture and accelerator design principles

Preferred Skills:

• Experience with GPU architectures and CUDA programming

• Background in accelerator functional modeling (TPU, NPU, DSP, or similar)

• Familiarity with Verilator, SystemVerilog, or RTL co-simulation (DPI interfaces)

• Knowledge of memory system modeling (HBM, DRAM, cache hierarchies)

• Experience with event-driven simulation frameworks (gem5, SST, or custom frameworks)

• Understanding of ML workloads and framework internals (PyTorch, TensorFlow)

• Background in optical computing, photonics, or analog computing paradigms

• Experience with high-performance simulation optimization techniques

• Python expertise for scripting, analysis, and test infrastructure

• Publication record in hardware modeling or computer architecture

What We Offer:

• A pivotal role in an innovative startup redefining the future of AI hardware.

• A collaborative and intellectually stimulating work environment.

• Competitive compensation, including salary and equity options.

• Good benefits - health, vision, dental, 401 (k), etc.

• Opportunities for career growth and future team leadership.

• Access to cutting-edge technology and state-of-the-art facilities.

• Opportunity to publish research and contribute to the field of efficient AI inference.

This is a rare opportunity to work on a game-changing technology at the intersection of photonics and AI. As part of our elite team, you’ll contribute to a platform that redefines computational performance and accelerates the future of artificial intelligence. Be a key player in bringing this transformative innovation to the world.