Modeling and Simulation Engineer (Optical)
Confirmed on the employer's own hiring board on Oct 24, 2026. First seen by Alion on May 13, 2026. Furientis scores A on the Alion truth index.
About the Team
The Seeker Team builds the eyes and the targeting logic of our weapon system: a low-cost, mass-producible, multimodal missile seeker that leans on commercial supply chains where they outperform, and vertically integrates wherever possible. On a modern missile, the seeker is 40 to 60% of unit cost and often drives overly long delivery cycles; accordingly, the seeker team is at the tip of the spear for delivering capability to our customers and value to the taxpayer.
Seeker design has exactly two real constraints: physics and mission. Nothing else is a show-stopper, only an obstacle to overcome. We are a small, deeply technical team that drives capability through ingenuity and bias for action and ships hardware that flies. This is a wear-many-hats environment where you must be comfortable "building the airplane in flight" and stepping well outside your comfort zone; a narrowly scoped role with clean handoffs is not what this team offers.
This is an AI-native team. Through fluent use of cutting-edge agentic coding tools, one engineer here consistently out-delivers a much larger conventional team. You will have opinions about where these tools help and where they do not, provide governance input, and build out an AI-centric workflow from day one.
About the Role
You build the team's real-time, physics-based engagement simulation and the target signature models used in it. You also build the end-to-end performance model from photon to processed image. That model predicts what the seeker will see before the hardware is designed or purchased. After every test and flight, it accounts for the difference between that prediction and the measured data. You work in tight partnership with the Seeker Data and Tooling Engineer, who builds the training-data pipeline and the compute under that simulation. You determine whether a rendered photon is physically correct. They build the machinery that turns that physics into datasets and throughput.
What You'll Do
Own the team's real-time, physics-based engagement simulation pipeline: scene, sensor, signal chain, and engagement logic, correct at speed.
Build and validate signature models for target hardbody and plume/exhaust phenomenology.
Own scene generation physics: DTED and georeferenced terrain, frames, projections, and accuracy budgets.
Model the aero-optical environment at Mach 3 speeds and reconcile it with the optical error budget.
Build and maintain end-to-end seeker performance models spanning scene, atmosphere, optics, FPA, ROIC, ADC, signal chain, and image processing in MWIR and LWIR.
Run Monte Carlo trade studies on optical, sensor, and signal-chain parameters and translate the results into program-level design decisions.
Validate models against captured imagery from lab, ground, and flight tests, and hold physics sign-off on every synthetic dataset the algorithms team trains against.
Skills We're Hiring For
B.S. in Optical Engineering, Physics, EE, Aerospace, or related; M.S. or Ph.D. preferred.
5+ years of classical EO/IR modeling and simulation, validated against measured sensor data.
MWIR/LWIR phenomenology: target signatures, atmospheric propagation, plume radiometry, and backgrounds.
Radiometry and sensor-chain modeling from first principles, photon budget to digital counts.
Modern Python for science and engineering; Git-based version control, with changes integrated through a CI/CD pipeline.
Bonus Points For
RF or radar M&S for multimodal sensor-fusion programs.
Aero-optical or hypersonic/supersonic flow-field modeling.
Hardware-in-the-loop or scene-projection (DMD, IRSP) experience.
CUDA and GPU programming experience.
Direct missile, munition, seeker, or guidance program experience.
Hands-on with MODTRAN, MUSES, DIRSIG, or an equivalent scene/atmosphere toolchain.
Sensor performance modeling with NV-IPM or equivalent.
Monte Carlo methods and statistics: designing trade studies and defending conclusions.
Daily use of agentic coding tools (Claude Code or similar) for model development and trade-study automation.
Unreal Engine, Unity, or similar engine experience.
Blender or similar 3D object rendering software.