below marketmost similar roles pay hereabove market
This role pays more than
74%
of similar roles. Most pay
$166,200–$222,500
— the blue band above.
At the midpoint, this role pays about
$222k
versus about
$194k
for comparable roles.
Based on 240 similar postings.
Employer
About Anduril Industries
Anduril Industries is a defense technology company that builds advanced hardware and software systems for national security, including autonomous drones, surveillance systems, and the Lattice AI command platform.
Anduril Industries currently has
901 open roles
on FindRole.
Listed pay typically runs
$166,000–$220,000
across 858 roles with salary data.
The Senior Numerical Optimization Engineer joins the Maritime Digital Production team to own the scheduling optimization core for shipbuilding factories. You will formulate shipyard production as a mathematical optimization problem, accounting for precedence, spatial exclusion, and resource constraints. Your daily work involves building and benchmarking solvers to generate stable, real-time replans for manufacturing operations. You will develop two-tier replan paths, establish solution-quality metrics, and research decomposition, metaheuristics, and non-traditional hardware like quantum annealing. Required expertise includes numerical optimization, linear programming, mixed-integer linear programming, and constraint programming. You must be proficient in Python, NumPy, SciPy, and Pandas, with experience using solvers like Gurobi, CPLEX, or OR-Tools. This role solves the NP-hard problem of resource-constrained project scheduling to digitize the manufacturing lifecycle for heavy metal production.
Formulate shipyard production scheduling as a mathematical optimization problem covering precedence, spatial exclusion, and resource constraints.
Own the solver-agnostic scheduling interface and benchmark commercial and open-source solvers for makespan and stability.
Build a two-tier replan path featuring fast local repairs and background global re-solves.
Develop stability objectives to prevent unnecessary work movement and determine when a better plan justifies the churn.
Establish performance metrics like LP relaxation lower bounds and quality ratios to define "good enough" solutions.
Research and evaluate advanced methods including decomposition, metaheuristics, and non-traditional hardware like quantum annealing.
Convert disruption events into replans by determining blast radius, scoping re-solves, and merging results into the live schedule.
Write production-quality code with comprehensive tests and instrument systems to make solution quality observable.
What we're looking for
5+ years of experience building production software 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.
Demonstrated ability to formulate real-world problems as mathematical models and implement them into production systems.
Hands-on experience with optimization solvers and libraries such as Gurobi, CPLEX, OR-Tools, SCIP, PuLP, CVXPY, or Pyomo.
Expert proficiency in Python for scientific computing and robust software development using NumPy, SciPy, and Pandas.
Strong theoretical and practical grounding in graph algorithms, constraint satisfaction, and computational complexity analysis.
Experience building reliable systems under operational constraints like high availability, latency budgets, or degraded inputs.
Advanced degree in Operations Research, Applied Mathematics, Computer Science, Industrial Engineering, or a related quantitative field, or equivalent practical depth.
U.S. Person status is required to access export-controlled data.
Ph.D. in Operations Research, Applied Mathematics, or a related field with publications or production work in scheduling (preferred).
Experience with resource-constrained project scheduling (RCPSP), job shop scheduling, or precedence-constrained scheduling in production (preferred).
Experience with dynamic or online rescheduling, including replanning under uncertainty and rolling-horizon methods (preferred).
Experience with metaheuristics (genetic algorithms, simulated annealing, tabu search, large neighborhood search) and decomposition methods (preferred).
Experience with performance-critical implementation in C++ or Rust for optimization kernels or hot-path graph traversal (preferred).
Familiarity with graph databases or large in-memory graph representations at 100K+ nodes (preferred).
Experience in manufacturing, industrial, or OT-adjacent domains, including familiarity with BOM, MES, ERP, PLM, or APS systems (preferred).
Exposure to non-traditional optimization hardware like GPU-accelerated solvers, HPC, or quantum annealing (preferred).
Experience in hyper-growth startup environments balancing speed, ambiguity, and long-term system health (preferred).
Familiarity with frontier AI tooling and AI-enabled software development workflows (preferred).
Experience in shipbuilding, aerospace, or complex discrete manufacturing (preferred).
Eligible to obtain and maintain a U.S. Secret security clearance (preferred).
EDR
Gen AI Security
SIEM
Threat Hunting
Security Architecture
Penetration Testing
Red Teaming
Incident Response
Computer Forensics
Endpoint Security
Detection Evasion
Proof of Concept
Proof of Value
EDR
Gen AI Security
SIEM
Threat Hunting
Security Architecture
Penetration Testing
Red Teaming
Incident Response
Computer Forensics
Endpoint Security
Proof of Concept
Proof of Value