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ABOUT THE TEAM
Anduril Labs is a multidisciplinary team of technologists, solution architects, engineers, and military subject matter experts. Its mission is to drive innovation across all Anduril business units and product lines by developing novel concepts and next-generation technologies that enhance Anduril's competitive edge and give its customers a decisive technological advantage over its adversaries.

ABOUT THE JOB
We are looking for a talented mid-level Software Engineer with a strong background in optimization to join our growing team at Anduril Labs. In this role, you will be instrumental in developing advanced algorithms and software solutions to tackle complex, multi-domain optimization problems critical to national defense and Anduril's autonomous systems.
The ideal candidate possesses deep expertise in classical optimization algorithms, robust Python programming skills, and a solid foundation in data modeling. Experience with developing hybrid quantum optimization solutions is a plus. You will leverage state-of-the-art, GenAI-powered development tools such as Claude Code to accelerate solution development and enhance our optimization software. This role demands creative problem-solving, a self-starter mentality, and the ability to rapidly apply algorithmic theory and mathematic modeling to practical, real-world optimization challenges. You will be designing, implementing, and deploying optimization algorithms and services that integrate seamlessly into larger defense systems, working across various platforms (on-prem, cloud, and hybrid quantum computing environments). Familiarity with modeling linear and non-linear optimization problems, rapid prototyping, integrating optimization solutions into existing architectures, leveraging APIs, and utilizing open-source tools will be crucial.
If you thrive in a dynamic environment that values creative problem-solving, love writing code, excel as both an individual contributor and team player, are eager to learn, and bring a can-do attitude, this role is for you.

• Design, develop, and implement highly efficient optimization algorithms and software solutions to solve challenging problems in areas such as resource allocation, scheduling, routing, mission planning, control systems, and supply chain logistics.
• Apply classical optimization techniques (e.g., linear programming, mixed-integer linear programming, combinatorial optimization, network flow, dynamic programming, heuristics, metaheuristics) to model and explore novel approaches.
• Utilize GenAI tools (e.g., OpenAI Codes, Claude Code, GitHub Copilot) to rapidly prototype, refine, and test algorithmic solutions, improving development velocity and code quality.
• Develop robust data models and efficient data pipelines to support complex optimization problems, ensuring data integrity and efficient processing for algorithmic inputs and outputs.
• Collaborate with multidisciplinary teams (software engineers, data scientists, domain experts, product managers) to integrate optimization engines and services into larger defense systems and platforms.
• Perform rigorous testing, validation, and performance analysis of optimization solutions, ensuring scalability, reliability, and accuracy under diverse operational conditions.
• Participate actively in the entire Software Development Lifecycle (SDLC) from requirements gathering and design to deployment, monitoring, and maintenance.
• Support Anduril- and customer-funded R&D efforts, contributing to technical documentation, presentations, and patent applications.

• Bachelor's degree in Computer Science, Software Engineering, Applied Mathematics, Operations Research, or a related quantitative field.
• 3+ years of professional experience in software development with a dedicated focus on optimization, algorithmic problem-solving, or operations research.
• Experience solving optimization problems in defense, transportation, supply chain, logistics, network optimization, smart grids or similar
• Expert proficiency in Python for scientific computing and robust software development.
• Strong theoretical and practical understanding of classical optimization algorithms (e.g., linear programming, mixed-integer linear programming, constraint programming, network flow, dynamic programming, heuristics, meta heuristics).
• Hands-on experience with optimization libraries and commercial/open-source solvers (e.g., SciPy Optimize, PuLP, CVXPY, Gurobi, CPLEX, OR-Tools, GEKKO). Experience with Gurobi is a plus.
• Solid experience with data modeling, data structures, and algorithms to efficiently prepare, process, and manage data for optimization problems.
• Demonstrable hands-on experience using GenAI tools (e.g., OpenAI Codex, Claude Code, Gemini Code Assist, GitHub Copilot, Amazon CodeWhisperer, or similar) for software development, code generation, debugging, and algorithmic exploration.
• Proficiency in using numerical computing libraries such as NumPy, SciPy, and Pandas.
• Demonstrated understanding and application of software testing principles and practices, including unit testing, integration testing, and end-to-end testing.
• Ability to develop, test, and deploy software effectively on Linux-based systems.
• Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance.
• Experience with Git version control, build tools, and CI/CD pipelines.
• Strong problem-solving skills, meticulous attention to detail, and the ability to work effectively in a collaborative team environment.
• Excellent communication and interpersonal skills, with the ability to effectively articulate complex technical concepts to diverse audiences.

• • Master's or Ph.D. in Computer Science, Applied Mathematics, Operations Research, or a closely related quantitative field.
  • Familiarity with or a strong interest in quantum optimization algorithms, quantum computing concepts, or quantum-inspired heuristic approaches. Experience with D-Wave's quantum annealing platform is a plus.
  • Experience with performance-critical programming languages such as C++ or Java.
  • Experience with cloud platforms (e.g., AWS, Azure, GCP) for deploying scalable optimization solutions or high-performance computing (HPC) environments.
  • Prior experience in defense, aerospace, logistics, supply chain management, robotics, or manufacturing optimization domains.
  • Familiarity with integrating machine learning models with optimization techniques (e.g., prescriptive analytics, reinforcement learning for optimization).
  • Excellent communication skills with the ability to articulate complex technical concepts, present findings, and influence technical direction across diverse teams.
  • Willingness to travel up to approximately 10%.