At Zone 5 Technologies, we're redefining what's possible in precision weapons and unmanned aircraft systems (UAS). Our team of engineers and innovators are developing cutting-edge autonomous solutions to deliver affordable and scalable precision weapons, interceptors, and UAS.

We're building the next generation of munitions and unmanned systems for the United States and its allies. If you're driven by hard problems, energized by rapid innovation, and ready to make an impact on defense technology, you belong here.

We are seeking a Senior Robotics Perception Engineer to serve as the perception technical lead embedded within a program team, developing seeker, target state estimation, and world modeling capabilities on top of our common AI/ML platform. You will own perception architecture and delivery for the program while contributing reusable capabilities back to the platform, working across the full pipeline from sensor data to actionable world state consumed by autonomy and mission software.

Responsibilities:

Target State Estimation & Seeker Systems

Design and develop target detection, tracking, and state estimation pipelines that produce robust track kinematics under challenging observation conditions
Implement track initiation, maintenance, association, and termination logic with well-characterized uncertainty
Develop and tune nonlinear state estimators (EKF, UKF, particle filters) for target motion modeling
Characterize seeker performance across engagement geometries, environmental conditions, and target signatures
Define confidence and covariance outputs that downstream autonomy can reason about

World State Modeling & Multi-Source Fusion

Architect the world state representation that fuses self-state, target tracks, terrain, threats, and mission context into a coherent model
Integrate outputs from VIO/SLAM, sensor fusion, and target tracking into a unified perception picture
Manage temporal alignment, coordinate frames, and data association across heterogeneous sensor streams
Define perception-to-autonomy interfaces with clear semantics for state, uncertainty, and freshness

Autonomy Integration & System Architecture

Own the perception architecture for the program and drive alignment with autonomy, guidance, and mission software teams
Design DDS topic structures and message contracts for perception outputs within a WOSA-aligned architecture
Build ROS2 nodes and libraries that expose perception capabilities through clean, versioned interfaces
Contribute reusable perception components back to the common AI/ML platform for use across programs
Balance program-specific customization against platform-level standardization

Embedded Performance & Deployment

Develop and optimize perception code in C++ for deterministic performance on embedded compute
Profile compute, memory, and I/O to meet real-time constraints on resource-limited platforms
Make architectural decisions about what runs on GPU, CPU, or dedicated accelerators
Support integration, hardware-in-the-loop testing, and field validation of perception subsystems

Technical Leadership

Write technical design documents, RFCs, and trade studies that drive perception architecture decisions
Mentor junior perception engineers through code review, pairing, and technical direction
Represent perception in program-level technical reviews and cross-team planning
Translate program requirements into perception subsystem requirements with measurable acceptance criteria

Qualifications:

Bachelor's in Robotics, Aerospace Engineering, Computer Science, Electrical Engineering, Applied Mathematics, or related field (Master's preferred) – equivalent industry experience also welcome
6-9+ years of experience in robotics perception, state estimation, or sensor fusion
Strong proficiency in modern C++ for real-time embedded systems, with an emphasis on determinism, memory discipline, and performance
Hands-on experience with ROS2 and DDS-based middleware in production or program-delivered systems
Demonstrable experience developing and tuning nonlinear state estimators (EKF, UKF, or particle filters) for real applications