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Senior Industrial Engineer, Simulation

Anduril· Manufacturing : Manufacturing Engineering : Industrial Engineering
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Costa Mesa, CA$146k - $194kfull-timePosted 1mo ago

About the role

Senior engineering role owning and scaling Anduril's factory simulation capability across the production ecosystem, from central service to manufacturing development planning, to drive capital, capacity, staffing, and ramp decisions with validated, long-lived models.

Responsibilities

  • Own Anduril’s discrete event simulation and operations-research capability for manufacturing line design as a long-lived, foundational asset — architecting it for maintainability, extensibility, and a high useful lifetime rather than single-use analysis. Work closely with IT and Tech Teams to integrate into existing business systems.
  • Build and manage the simulation intake and prioritization process — a centralized system for receiving, scoping, and triaging simulation requests from across the organization, ensuring the highest-impact studies are resourced first and stakeholders have visibility into the pipeline.
  • Define how and where simulation is used at varying levels of NPI maturity within the MDP process: from early-stage concept models that inform layout and line design decisions, through mid-maturity models that validate rate-readiness and identify bottlenecks, to mature production models that confirm the line will perform at target rate before committing capital and labor.
  • Work closely with material flow, layout, labor standards (cycle times), manufacturing test design, and automation teams — consuming their validated inputs to build simulation models that reflect the integrated production system, not isolated processes.
  • Capture current and planned processes — physical constraints, business rules, and detailed decision logic — into validated simulation models that serve as a living, “current-status” reference for determining future factory and supply-chain performance across transformation projects and investment decisions.
  • Design the data pipeline that keeps models current: define how live production data flows in so models continuously reflect reality and can generate updated, feasible production plans and schedules as conditions change.
  • Select and apply the right method for the question — baseline capacity analysis, discrete event simulation, Monte Carlo, and statistical/optimization models — and justify why a given approach fits the decision at hand.
  • Lead the highest-stakes simulation studies: capacity modeling, NPI ramp simulation, capital-investment analysis with quantified ROI, line balancing and flow optimization, design-change impact analysis, and production risk/scenario planning.
  • Drive ROI calculations and impact analysis for major investment decisions — test equipment purchases, automation investments, facility moves or reconfigurations — using simulation to quantify the before/after and give leadership a defensible basis for committing capital.
  • Own the design of new production lines and workstation layouts for both low-rate and full-rate production, using a data-driven, simulation-backed approach.
  • Proactively identify high-variation processes, imbalances, and bottlenecks caused by layout, equipment, staffing, or other production inputs; flag constraints with the appropriate owners and drive them to resolution.
  • Turn simulation output into decisions: quantify the distribution of outcomes, stress-test ramp plans, and give leadership a clear, defensible recommendation with the uncertainty attached.
  • Establish the standards: validation against actuals, version control, assumption tracking, calibration methods, and a repeatable methodology from scope to hand-off.
  • Hand off mature, validated line models to sustaining IEs and production planning for ongoing planning, staffing decisions, ramp modeling, and schedule optimization.
  • Make models digestible to non-specialists — build interfaces, dashboards, and documentation for self-serve decision making.
  • Drive migration of legacy planning tools onto a centralized platform to unify planning against one source of truth.
  • Establish how the team leverages AI to move faster without sacrificing rigor, including guardrails for validation of AI-generated work.
  • Mentor and train engineers to raise the standard of simulation and operations-research practice across manufacturing.

Qualifications

  • 6+ years of experience building simulation and/or operations-research models used to drive real operational or capital decisions in a fast-paced manufacturing environment.
  • Deep, hands-on expertise with discrete event simulation software (e.g., Siemens Tecnomatix Plant Simulation, Simio, FlexSim, AnyLogic, Arena, ProModel, SimPy, or equivalent) and a strong grasp of underlying statistics.
  • Working command of complementary analytical methods: capacity and bottleneck analysis, Monte Carlo, regression, and mathematical optimization (linear/integer programming).
  • Strong programming ability (Python, SQL) for building data pipelines, custom models, and reproducible analysis, with comfort working with large data sets.
  • Ability to read technical documentation such as facility drawings, assembly drawings, technical specifications, and manufacturing procedures for electronic, mechanical, and electromechanical assembly.
  • Track record of building analytical tools that others actually used and maintained with longevity, data freshness, validation, and end-user consumption in mind.
  • Ability to work in ambiguity and communicate uncertainty, translating technical output into clear recommendations for non-technical decision-makers.
  • Must be a U.S. Person due to required access to U.S. export-controlled information or facilities.

Skills

Required:Discrete event simulationPythonSQLCapacity/bottleneck analysisData integrationCommunication to non-technical stakeholders
Nice to have:Monte CarloOptimization (linear/integer programming)Leadership/mentoring

Benefits

  • Competitive benefits package (health, recovery, and other coverage)
  • Top-tier benefits for full-time employees
  • Equity grants commonly included in total compensation package
Last updated Sep 9, 2026. Interested? Apply on the company site.

About Anduril

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