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We are looking for a Software Engineer with deep expertise in Mathematical Optimization and quantum algorithm development. This role is critical in architecting the core software engine that drives our proprietary photonic quantum processors, combining complex mathematical formulations with physical optical hardware feedback.
Job Responsibility
Design and implement the high-performance C++ runtime and Hardware Abstraction Layer (HAL) for photonic optimization computers
Profile and optimize critical execution paths to minimize latency, addressing bottlenecks in memory bandwidth, cache locality, and data transfer
Collaborate with FPGA, Electrical engineers and Firmware engineers to ensure to create, test, and optimize device interfaces
Develop algorithmic enhancements to usage of quantum feedback to solve NP hard optimization problems more efficiently with higher solution quality
Write efficient, thread-safe code for concurrent hardware control and real-time signal processing
Design and implement novel algorithms that map optimization and machine-learning problems onto entropy-based photonic quantum processors, including post-processing pipelines
Build software layers to decompose and orchestrate large-scale optimization problems across multiple photonic hardware resources
Contribute to quantum algorithms on the company roadmap
Requirements
6+ years of experience in software engineering with a focus on systems or HPC
Strong proficiency in C++ and Python
Experience with quantum algorithms, quantum information, or quantum optics
Strong mathematical background in Convex Optimization, Quadratic Programming (QP), Mixed-Integer Linear Programming (MILP), or Gradient-Free Methods
Experience with Numerical Analysis and high-performance math libraries (e.g., BLAS, LAPACK, Eigen)
Familiarity with protocols (e.g., UART, SPI, gRPC, REST) and software integration
Strong understanding of performance tuning, memory management, and fault-tolerant design
Familiarity with Linux system programming and build toolchains (CMake, GCC/Clang)
Experience working in cross-functional teams involving hardware, physics, and software.
Nice to have
Advanced degree (MS/PhD) in Computer Science, Physics, or Mathematics
Experience with classical optimization solvers (e.g., CPLEX, Gurobi) or heuristic frameworks
Familiarity with Open Quantum Systems or optical feedback mechanisms
Background in Digital Signal Processing (DSP) or control theory
Knowledge of containerized deployment using Docker.