Senior Staff Software Engineer, Perception (R4985)

Shield; Washington (District of Columbia); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Equity

Bonus

Benefits

Job summary

Shield AI’s Hivemind Solutions Perception team seeks an experienced ML engineer to develop and deploy state-of-the-art perception models for autonomous systems used in defense contexts. You will collaborate with researchers, engineers, and platform teams to translate research into reliable, production-ready capabilities for U.S.

and international customers. You will design, train, and optimize vision/vision-language models, build scalable data pipelines, and deploy models on embedded hardware

Qualifications

• Minimum 7–10 years of related experience with degree combinations as described.
• Mastery of machine learning fundamentals.
• Experience training and deploying ML models for computer vision in production.
• Strong understanding of 3D vision problems/algorithms.
• Proficiency in C++ and Python.
• Ability to obtain a SECRET clearance.

Responsibilities

• Model Development– design, train, fine-tune, and maintain vision/vision-language models.
• Data Pipelines & Model Training– build scalable data pipelines and evaluation loops.
• Model Deployment & Optimization– deploy ML models for embedded hardware with ONNX/TensorRT.
• Perception & Autonomy Applications– apply ML to autonomous systems in complex environments.
• Research-to-Production– balance performance, robustness, efficiency, and reliability.
• Cross-functional Collaboration– work with perception, autonomy, platform, and software teams.
• Model Evaluation & Validation– develop benchmarks and testing for failure modes.
• Continuous Improvement– improve training infra, tooling, and deployment workflows.

Skills

Machine learning fundamentals

C++

Python

PyTorch

TensorFlow

3D vision

Production ML deployment

Data pipelines

Education

Bachelor's degree in related field

Master's degree in related field

PhD in related field

Tools

ONNX

TensorRT

PyTorch

TensorFlow

Job description

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BATaircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.

The Hivemind Solutions Perception team develops the next generation of perception capabilities for autonomous systems by combining state-of-the-art machine learning with the proven foundations of computer vision. The team advances how autonomous platforms understand and interpret the world by developing vision, vision-language (VLM), and vision-language-action (VLA) models that tackle core perception challenges such as object understanding, scene interpretation, and mission-relevant environmental awareness. Working at the intersection of research and production, our engineers build the data pipelines, supervised fine-tuning (SFT) workflows, evaluation frameworks, and deployment infrastructure needed to transform cutting-edge AI research into reliable, mission-ready perception capabilities.

In this role, you’ll develop and deploy advanced machine learning models that enable autonomous systems to better understand, reason about, and interact with their environment. You’ll partner closely with machine learning researchers, autonomy engineers, perception engineers, and platform teams to translate emerging AI capabilities into reliable, production-ready systems for U.S. and international defense customers. This is an ideal opportunity for engineers who enjoy building state-of-the-art AI systems while solving the practical challenges of deploying them on operational autonomous platforms.

What You’ll Do:

• Model Development– Design, train, fine-tune, and maintain state-of-the-art vision, vision-language, and vision-language-action models that improve perception and decision-making for autonomous systems.
• 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.

Required Qualifications:

• Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 9 years and a Master’s degree; or 7 years with a PhD; or equivalent work experience.
• Mastery 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

Preferred Qualifications:

• 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 recordof publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA).

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#LE

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.

Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed toequal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.