Job Description:

Shield AI's Hivemind Detection, Tracking, and Mapping (DTM) team develops perception capabilities that allow autonomous systems to understand objects, motion, sensors, and terrain across air, maritime, and ground domains. We are seeking a Staff Engineer to develop these capabilities from algorithms and production C++ libraries through integration, verification, and delivery in the Hivemind SDK.

This is a full-stack perception product-development role. You will bring depth in at least one core area such as object detection, object tracking, computer vision, image processing, sensor modeling, or sensor fusion, and work comfortably across adjacent parts of the stack. You will help turn prototypes, research, and partner-developed technology into reusable, configurable, well-tested product capabilities.

What you'll do:

• Design and implement production perception capabilities in modern C++, with emphasis on clear interfaces, correctness, performance, maintainability, and automated test coverage.
• Own features across the development lifecycle: clarify requirements, evaluate technical approaches, develop algorithms and libraries, integrate them into the Pilot runtime, and carry them through SDK validation, documentation, and release readiness.
• Contribute deep technical judgment in one or more DTM areas, including object detection, object tracking, computer vision, image processing, sensor and measurement modeling, mapping, or multi-sensor fusion.
• Work across adjacent layers such as sensor data contracts, coordinate frames, timing, configuration, simulation, replay, analyzers, embedded deployment, and end-to-end perception workflows.
• Diagnose difficult system behavior using source code, logs, recorded sensor data, simulation, and focused experiments; drive issues from symptom through root cause, corrective action, and regression coverage.
• Participate in design reviews and code reviews, communicate technical tradeoffs concisely, mentor other engineers, and help improve the architecture and engineering practices of the DTM stack.
• Use modern AI-assisted engineering tools effectively while remaining accountable for the design, technical accuracy, security, test coverage, and reviewability of the resulting work.
• Evaluate how emerging foundation-model capabilities may strengthen detection, tracking, image understanding, simulation, and perception workflows, and help identify practical paths from promising technology to dependable product capability.

Required qualifications:

• Significant professional experience developing and delivering production C++ software for robotics, autonomy, perception, real-time systems, simulation, or another complex technical product.
• Deep experience in at least one relevant technical area, such as object detection, object tracking, computer vision, image processing, sensor modeling, sensor fusion, estimation, or mapping.
• Demonstrated ability to work beyond a prototype or isolated algorithm and deliver maintainable software with clear interfaces, tests, diagnostics, documentation, and integration into a larger system.
• Strong debugging and systems-thinking skills, including the ability to reason across algorithms, software architecture, data contracts, configuration, timing, coordinate frames, compute behavior, and sensor data.
• Proficiency with Python tools for technical analysis, visualization, experimentation, or verification.
• Experience collaborating across teams and disciplines, making sound technical decisions amid ambiguity, and communicating designs, risks, and review feedback clearly and constructively.
• Experience using-or the demonstrated ability to quickly adopt-modern AI-assisted development tools with disciplined human review and validation.

Preferred qualifications:

• Experience developing software for autonomous aircraft, maritime systems, ground robots, automotive systems, defense applications, or other operationally deployed robotic platforms.
• Experience with multi-target tracking, data association, estimation, multi-sensor or multi-agent fusion, angle-only tracking, or measurement modeling.
• Experience with EO/IR imagery, video pipelines, radar, LiDAR, GNSS/INS, camera models, calibration, or time-aligned sensor data.
• Familiarity with embedded Linux, edge or GPU compute, CUDA, TensorRT, NVIDIA Jetson, Qualcomm, or comparable deployment environments.
• Experience with simulation, hardware-in-the-loop testing, recorded-data replay, performance analyzers, or evaluation against real-world sensor data.
• Familiarity with modern C++ package, build, configuration, and CI systems such as CMake, Nix, Conan, GitLab CI, or comparable tooling.
• Practical familiarity with vision foundation models, vision-language models, learned visual representations, or the data and evaluation workflows needed to adapt foundation models to robotics and autonomy.
• Experience turning research, IRAD, partner-developed, or program-specific software into reusable product libraries and stable integration contracts.

This role is hybrid and based at Shield AI's San Diego, CA headquarters, with three days per week in the office as the baseline. Candidates currently outside San Diego who are willing to relocate are encouraged to apply.

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Full-time regular employee offer package:

Pay within range listed + Bonus + Benefits + Equity

Temporary employee offer package:

Pay within range listed above + temporary benefits package (applicable after 60 days of employment)

Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.