Optical Modeling and Simulation Engineer

America is critically deficient in production of defensive munitions- we currently produce shipborne interceptors in the few hundreds per year while our adversaries are producing offensive threats in the tens of thousands per year. Furientis was started to help solve this problem- introducing a new class of cost-effective, high production rate, interceptor missiles. We're seeking motivated individuals who internalize this problem and are eager to apply their past experience in similar industries (aerospace, defense, automotive/racing, robotics) and out of the box thinking to solve this problem for the US and its allies.

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.

You will be the responsible engineer for the synthetic-data pipeline and the end-to-end performance model that drive our seeker program. This is a hybrid role: half ML data engineer, half traditional defense modeling and simulation engineer. Your top priority is the production, validation, and management of training data the algorithms team trusts. Behind the pipeline sits the classical M&S work: scene generation, atmospheric propagation, optics, focal-plane response, signal chain, target signatures, and plume/exhaust phenomenology, that gives the imagery and the predictions their physics.

You will play an integral role in standing up the team's end-to-end, real-time, physics-correct engagement simulation pipeline. You report to the seeker lead, who carries final technical authority, and partner closely with the seeker hardware, algorithm, and GNC engineers. Your job is to make sure the trades, predictions, and datasets behind every design decision are rigorous, reproducible, and trusted.

• Produce, validate, and manage the synthetic and semi-synthetic image datasets the algorithms team trains and evaluates against, with disciplined provenance, ground truth, and metadata. This is the highest-priority output of the role
• 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
• Build and validate signature models for target hardbody and plume/exhaust phenomenology
• Stand up and own the team's real-time, physics-correct engagement simulation pipeline integrating scene, sensor, signal chain, and engagement logic
• Integrate DTED and other georeferenced terrain data into scene generation, with discipline around frames, projections, and accuracy budgets
• Run CPU and GPU compute at scale on cloud infrastructure to render imagery and produce datasets at the volumes the algorithms team needs
• Author CUDA-accelerated rendering and signal-chain kernels where simulation throughput demands it; profile and optimize end-to-end pipeline throughput on multi-GPU rigs
• Run Monte Carlo trade studies on optical, sensor, and signal-chain parameters (FPA choice, integration time, f-number, FOV, NETD/NEI) and translate results into…