About the Role
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.