Quantum Algorithms Engineer

We are seeking a Software Engineer with deep expertise in mathematical optimization and quantum algorithm development. This role focuses on building the core software stack that interfaces with advanced photonic and quantum-inspired computing hardware, combining rigorous mathematical methods with real-time system constraints and hardware feedback. Position Description We are looking for a Software Engineer with strong expertise in mathematical optimization and high-performance computing. This role is critical in architecting the core software engine that drives next-generation optimization and quantum-inspired computing systems, combining complex mathematical formulations with physical hardware feedback and real-time execution constraints. Responsibilities 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 create, test, and optimize device interfaces. Develop algorithmic enhancements to leverage quantum feedback for solving 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 or quantum-inspired processors, including post-processing pipelines. Build software layers to decompose and orchestrate large-scale optimization problems across multiple hardware resources. Contribute to quantum algorithms on the company roadmap. Required Qualifications 4+ 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. Preferred Qualifications 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. #J-18808-Ljbffr Lumicity