> Markdown version of [/jobs/ext/1599907-staff-software-engineer-perception-r5421](https://www.wearedevelopers.com/jobs/ext/1599907-staff-software-engineer-perception-r5421). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Staff Software Engineer, Perception (R5421)

- **Company:** Shield AI
- **Location:** Washington, DC, United States
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Computer Vision, C++ (Programming Language), Python (Programming Language), Machine Learning, Language Modeling, Tensorflow, Software Engineering, Strategies of Testing, Pytorch, Model Validation, SC Clearance, ONNX (Open Neural Network Exchange) Format, Machine Learning Operations, TensorRT, Multiaccess Edge Computing, Data Pipelines
- **Published:** July 28, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9063526/staff-software-engineer-perception-r5421

## About the Role

* Typically requires a minimum of 7 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or 4 years with a PhD; or equivalent work experience.

 * Expertise of machine learning fundamentals.

 * Experience training an deploying ML models for computer vision in a production setting.

 * Strong understanding of 3D vision problems/algorithms.

 * Experience with machine learning frameworks such as PyTorch and TensorFlow.

 * Demonstrated expertise in deploying models using TensorRT and ONNX.

 * Proficiency in C++ and Python.

 * Strong analytical and problem-solving skills, with the ability to translate research into practical applications.
 * Ability to obtain a SECRET clearance

 * Experience with developing autonomous systems for defense customers.

 * Experience with training/finetuning vision-language models, vision-language-action models, and/or world models.

 * Contributions to open-source projects in machine learning or computer vision.

 * Track record of publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA).

## Description

Data Pipelines & Model Training - Build scalable data pipelines, supervised fine-tuning (SFT) workflows, and evaluation loops that continuously improve model performance on mission-relevant tasks.

Model Deployment & Optimization - Deploy and optimize machine learning models for embedded hardware using technologies such as ONNX, TensorRT, and hardware-accelerated inference frameworks.

Perception & Autonomy Applications - Apply modern machine learning techniques to solve challenging perception and autonomy problems across aerial and other autonomous systems operating in complex, real-world environments.

Research-to-Production - Translate cutting-edge machine learning research into production-ready capabilities by balancing model performance, robustness, computational efficiency, and operational reliability.

Cross-functional Collaboration - Partner closely with perception, autonomy, platform, and software engineering teams to integrate machine learning capabilities into mission-ready autonomous systems.

Model Evaluation & Validation - Develop benchmarks, testing methodologies, and evaluation frameworks to measure model performance, identify failure modes, and guide future improvements.

Continuous Improvement - Improve training infrastructure, developer tooling, deployment workflows, and model lifecycle management to accelerate experimentation and production delivery.


## Related Videos

- [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated)
- [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs)
- [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding)
- [Robots are coming into the wild! Full-Stack Robotics Engineers, be ready!](https://www.wearedevelopers.com/videos/479-robots-are-coming-into-the-wild-full-stack-robotics-engineers-be-ready)
- [Developing an AI.SDK](https://www.wearedevelopers.com/videos/198-developing-an-ai-sdk)
- [Overview of Machine Learning in Python](https://www.wearedevelopers.com/videos/840-overview-of-machine-learning-in-python)

## Related Articles

- [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)
- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)
- [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)
- [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)
- [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)