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Anduril Industries is seeking a mid-level Software Engineer with deep expertise in optimization to join Anduril Labs, a multidisciplinary innovation team developing next-generation defense technologies. You will design, develop, and implement advanced optimization algorithms and software solutions to solve complex, multi-domain problems critical to autonomous defense systems and national security.
Key responsibilities include:
- Design and implement highly efficient optimization algorithms for resource allocation, scheduling, routing, mission planning, control systems, and supply chain logistics
- Apply classical optimization techniques including linear programming, mixed-integer linear programming, combinatorial optimization, network flow, dynamic programming, and metaheuristics
- Leverage GenAI-powered development tools (Claude Code, GitHub Copilot) to rapidly prototype and refine algorithmic solutions
- Develop robust data models and efficient data pipelines to support complex optimization problems
- Collaborate with multidisciplinary teams (software engineers, data scientists, domain experts, product managers) to integrate optimization engines into larger defense systems
- Perform rigorous testing, validation, and performance analysis to ensure scalability, reliability, and accuracy
- Participate in the full software development lifecycle from requirements gathering through deployment and maintenance
- Support R&D efforts with technical documentation, presentations, and patent applications
Required qualifications:
- Bachelor's degree in Computer Science, Software Engineering, Applied Mathematics, Operations Research, or related quantitative field
- 3+ years of professional software development experience with dedicated focus on optimization, algorithmic problem-solving, or operations research
- Experience solving optimization problems in defense, transportation, supply chain, logistics, network optimization, or similar domains
- Expert proficiency in Python for scientific computing and robust software development
- Strong theoretical and practical understanding of classical optimization algorithms
- Hands-on experience with optimization libraries and solvers (SciPy Optimize, PuLP, CVXPY, Gurobi, CPLEX, OR-Tools, GEKKO)
- Solid experience with data modeling, data structures, and algorithms
The ideal candidate is a creative problem-solver with a self-starter mentality, thrives in dynamic environments, excels as both individual contributor and team player, and brings a can-do attitude. Experience with hybrid quantum optimization solutions and Gurobi is a plus.
