Optimization Algorithms Jobs (NOW HIRING)

Maritime Digital Production (MDP) is the software and digital systems function within Anduril's Heavy Metal division. We build and deploy the full technology stack that powers Anduril's shipbuilding factories: the data infrastructure that makes every machine and sensor visible in real time, the manufacturing execution system (ArsenalOS) that workers and planners use every shift, the scheduling engine that replans production in minutes instead of days, and the AI systems that eliminate manual toil from both the shop floor and business operations.
MDP operates at the boundary between Operational Technology and Information Technology. Our systems live where factory-floor machines, edge compute, and OT networks meet enterprise platforms and cloud infrastructure. We incubate solutions close to the production line, validate them with real operators building real hardware, harden them for reliability and security, and then scale them across multiple sites. The environment is fast, physical, and consequential. When our systems go down, production stops. The output of our work is not a dashboard: it is a ship.
This is not a support function. It is a strategic investment by Anduril in the premise that digitizing the manufacturing lifecycle end-to-end, from engineering definition through scheduling through execution through field feedback, is how Heavy Metal will out-build, out-adapt, and out-scale the traditional defense industrial base. MDP is scaling from a founding team to 70+ engineers across multiple U.S. sites. You will be joining early, working on hard problems with real operational stakes, and shaping how manufacturing software is built at Anduril from the ground up.

As a Senior Numerical Optimization Engineer on the LOKI initiative, you will develop the scheduling and optimization algorithms that generate manufacturing precedence graphs from 3D geometry and BOMs. You will build systems that replan production schedules in under 10 minutes when disruptions occur, using constraint solvers, numerical optimization techniques, computational geometry, and graph algorithms to transform how ships are built.

• Design, develop, and implement advanced optimization algorithms that automatically generate manufacturing precedence graphs from 3D CAD geometry, bills of materials, and manufacturing process definitions.
• Build production scheduling systems that replan manufacturing operations in under 10 minutes when disruptions occur, using mixed-integer programming, constraint programming, and metaheuristic optimization techniques.
• Partner with manufacturing engineers and factory operators to understand production workflows and translate them into mathematical optimization models.
• Write production-quality code with comprehensive tests, participating in code review and architectural discussions.
• Apply computational geometry techniques to extract manufacturing dependencies, spatial constraints, and assembly sequences directly from CAD models and 3D geometry.
• Develop and implement graph algorithms that model complex manufacturing dependencies, resource constraints, tooling availability, and skill requirements across shipbuilding operations.
• Formulate and solve large-scale optimization problems using commercial and open-source solvers (e.g., Gurobi, CPLEX, OR-Tools, SCIP) to optimize makespan, resource utilization, and production flow.
• Deploy and operate your systems in factory environments, including edge compute clusters and OT networks.
• Perform rigorous testing, validation, and performance analysis of optimization solutions, ensuring sub-10-minute replanning times at production scale.
• Leverage AI tooling (coding assistants, automation) in your development workflow and contribute to team engineering practices.
• Join an on-call rotation supporting production factory systems.
• Collaborate with data engineers to integrate optimization engines with real-time factory data streams, PLM, ERP, and MES systems.

• 5+ years of experience in a software engineering role building production systems, ideally in a fast-paced environment.
• Deep expertise in numerical optimization, including linear programming, mixed-integer linear programming, constraint programming, combinatorial optimization, or metaheuristics.
• Strong technical fluency in modern software architectures, APIs, distributed systems, CI/CD, and cloud or edge infrastructure.
• Expert proficiency in Python for scientific computing and robust software development, with strong foundations in numerical computing libraries (NumPy, SciPy, Pandas).
• Hands-on experience with optimization libraries and commercial/open-source solvers (e.g., Gurobi, CPLEX, OR-Tools, SCIP, PuLP, CVXPY, Pyomo).
• Strong theoretical and practical understanding of constraint satisfaction, graph algorithms, and computational complexity analysis.
• Experience building systems that must operate reliably under real-world operational constraints (high availability, low latency, or constrained environments).
• Demonstrated ability to formulate real-world problems as mathematical optimization models and implement production-grade solutions.
• Excellent written and verbal communication skills, with the ability to collaborate across engineering, manufacturing, and operations teams.
• Degree in Computer Science, Applied Mathematics, Operations Research, Industrial Engineering, or related technical field, or equivalent practical experience.
• U.S. Person status is required as this position needs to access export controlled data.

• Experience in manufacturing, industrial, or OT-adjacent domains (MES, SCADA, PLC integration, factory automation, IoT).
• Master's or Ph.D. in Operations Research, Applied Mathematics, Computer Science, Industrial Engineering, or closely related quantitative field.
• Hands-on experience with computational geometry algorithms, CAD/CAM systems (STEP, IGES, OpenCASCADE), or 3D modeling APIs for manufacturing applications.
• Experience with production scheduling, job shop scheduling, resource-constrained project scheduling (RCPSP), or manufacturing optimization.
• Background in graph algorithms, network flow optimization, or precedence-constrained scheduling problems.
• Experience with heuristic and metaheuristic algorithms (genetic algorithms, simulated annealing, tabu search, ant colony optimization) for large-scale scheduling problems.
• Familiarity with frontier AI tooling, AI coding assistants, and AI-enabled software development workflows.
• Experience in hyper-growth startup-like environments, with demonstrated success balancing speed, ambiguity, and long-term system health.
• Familiarity with enterprise systems such as ERP, MES, WMS, PLM, or advanced planning and scheduling (APS) systems.
• Experience with performance-critical programming languages such as C++, Rust, or Java for optimization kernels.
• Experience in manufacturing industries with hands-on exposure to assembly lines, shipbuilding, aerospace, or complex discrete manufacturing.
• Knowledge of Bill of Materials (BOM) structures, manufacturing routing, work centers, and production planning concepts.
• Experience with real-time optimization, online algorithms, or dynamic rescheduling under uncertainty.
• Eligible to obtain and maintain a U.S. Secret security clearance.