The demand for new datacenters and AI compute is rapidly outpacing the planet's energy capacity. Digital solutions are hitting a power wall as we approach the physical limits of traditional silicon. Conquering this bottleneck isn’t about bigger chips or more of them; it means rethinking the fundamental architecture. The industry's current path isn’t going to meet the need, so we took a different approach.
Instead of traditional electronic circuits, we use silicon photonics and an active, programmable metasurface to perform matrix multiplications at the speed of light. Our optical cells are 10,000x smaller than traditional photonic components, enabling unprecedented density. By using photonics instead of electricity, our chips become more efficient as they scale. This architecture will deliver up to 100 times the energy efficiency of existing solutions while significantly improving performance for large-scale AI inference.
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 computing!
Position Overview:
We are seeking a talented ML Compiler Engineer to join our engineering team and lead the development of our compiler. This role focuses on compiler development for our novel LLM accelerator architecture. This is one of several software stacks that seamlessly bridge high-level AI workloads with our custom hybrid optical-electronic compute hardware, enabling customers to realize game-changing performance.
Location: Austin, TX. Full-time onsite position.
Key Responsibilities:
Design and implement toolchains for our custom LLM accelerator architecture
Develop optimization strategies that bridge software algorithms to hardware implementations
Design and implement custom compiler components, including IR dialects, graph transformations, and lowering passes
Optimize computational graphs and memory access patterns for our hardware architecture
Integrate with existing ML frameworks (e.g., PyTorch, JAX, Triton).
Build and maintain test infrastructure to ensure compiler correctness and performance
Qualifications:
Bachelor's degree in Computer Science, Computer Engineering, or related field
10+ years of industry experience
5+ years of professional experience in systems programming or compiler development
Expert-level proficiency in Python and C
Experience with hardware compilers
Familiarity with Large Language Model architectures and their computational requirements
Hands-on experience with compiler frameworks and code optimization techniques
Deep understanding of computer architecture, memory hierarchies, and parallel computing concepts
Experience with AI/ML accelerators (GPUs, TPUs, FPGAs) and their programming models
Preferred Skills:
Master's degree in Computer Science, Computer Engineering, or related field
Strong background in graph theory and graph transformations in a compiler or optimization context; MLIR experience is a plus
Experience writing programs that parse, analyze, and mutate programs as abstract syntax trees
Experience in instrumenting and debugging parallel programs
Experience with structured, human-supervised AI/agentic coding workflows
Experience with LLM quantization techniques and model optimization
Experience with high-performance computing and low-latency system design
Familiarity with deep learning frameworks and neural network optimization
Technical Skills
Programming Languages: Python and C (essential), Assembly
Compiler Frameworks: LLVM, MLIR, GCC, custom backend development
Graph Theory: Graph algorithms, graph rewriting systems, DAG optimization
AST Processing: Parsing, analysis, and transformation of abstract syntax trees
Testing & QA: pytest, GoogleTest, or similar frameworks; static analysis tools
CI/CD: Jenkins, GitHub Actions, GitLab CI, or similar systems
LLM Technologies: Transformer architectures, attention mechanisms, quantization techniques
Development Tools: CMake, Git, Docker
Parallel Tools: Profilers, debuggers, and instrumentation for parallel/concurrent programs
Technical Environment
Languages: Python and C (primary), Assembly for low-level optimization
Compiler Tools: LLVM, MLIR, GCC, custom compiler backends
Testing: Automated test suites, continuous integration pipelines
Frameworks: PyTorch/JAX/Triton integration, custom inference engines
Focus Areas: Compiler backend development, optimization passes, hardware-software co-design
This is an opportunity to play a pivotal role in an innovative startup redefining the future of AI hardware. Work on a game-changing technology at the intersection of photonics and AI as part of a collaborative and brilliant team. You’ll contribute to a platform that redefines computational performance and accelerates the future of artificial intelligence. Come help us bring this transformative technology to the world.
BenefitsJoin a team that invests in your future and your well-being. At Neurophos, we offer:
100% coverage of base health plan premiums for you and your dependents, plus HSA contributions.
Unlimited PTO. No rigid vacation banks, just a focus on delivery.
401(k) matching and stock option opportunities to ensure our success is your success.
Full suite of voluntary benefits, including Dental, Vision, Life, Hospital, Critical Illness, and Accident insurance.
Personalized Benefits. Choose the plans that fit your life and take the cash back for those that don’t.
Top Skills
What We Do
Neurophos is delivering the computational power of the human brain to artificial intelligence. By leveraging decades of metamaterials research and >300 patents, we are unlocking the speed and efficiency of optical compute in an in-memory processor to increase the speed and energy efficiency of AI inference by more than 100X.
