Senior Software Engineer, Perception (R5420)

Shieldai; Washington (District of Columbia); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Equity

Bonus

Benefits

Job summary

Shield AI is actively hiring engineers to develop and deploy advanced machine learning models for perception in autonomous systems. You will own features from development through deployment, collaborating with researchers, perception engineers, autonomy engineers, and platform teams to bring cutting‑edge AI into production on autonomous platforms.

The role emphasizes vision and 3D perception, data pipelines, SFT workflows, evaluation frameworks, and deployment infrastructure, with a focus on

Qualifications

• Minimum 5 years of related experience with a degree; or 4 years + Master; or 2 years + PhD; or equivalent work experience.
• Proficiency in machine learning fundamentals and production ML for computer vision.
• Experience deploying ML models for defense or autonomous systems is preferred.
• Strong understanding of 3D vision problems and algorithms.
• Hands-on experience with PyTorch and TensorFlow; deployment with TensorRT and ONNX.
• Proficiency in C++ and Python; ability to translate research into practical applications.
• Ability to obtain a SECRET clearance.

Responsibilities

• Model Development – Design, train, fine-tune, and maintain state-of-the-art vision, vision-language, and vision-language-action models.
• Data Pipelines & Model Training – Build scalable data pipelines and evaluation loops to improve model performance.
• Model Deployment & Optimization – Deploy ML models for embedded hardware using ONNX, TensorRT, and related frameworks.
• Perception & Autonomy Applications – Apply ML to perception and autonomy challenges across aerial and autonomous systems.
• Research-to-Production – Balance performance, robustness, efficiency, and reliability.
• Cross-functional Collaboration – Work with researchers, perception engineers, platform teams to integrate ML into systems.
• Model Evaluation & Validation – Develop benchmarks, testing methodologies, and evaluation frameworks.
• Continuous Improvement – Improve training infrastructure, tooling, workflows, and lifecycle management.

Skills

Machine learning fundamentals

C++

Python

PyTorch

TensorFlow

Vision/3D vision

Model deployment

Data pipelines

Problem solving

Clearance (SECRET)

Education

Bachelor's degree in CS/EE/ML or related field

Tools

PyTorch

TensorFlow

TensorRT

ONNX

C++

Python

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.

TheHivemindSolutions Perception team develops the next generation of perception capabilities for autonomous systems by combiningstate-of-the-artmachine 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 transformcutting-edgeAI research into reliable, mission-readyperceptioncapabilities.

In this role, you'll develop and deploy advanced machine learning models that solve real-world perception challenges for autonomous systems. You'll own major features from model development through deployment, working closely with machine learning researchers, perception engineers, autonomy engineers, and platform teams to bring cutting-edge AI capabilities into production. This is an ideal opportunity for engineers who enjoy solving difficult perception problems while building reliable, production-ready ML systems that operate on autonomous platforms in complex operational environments.

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.

• Typically requires a minimum of 5 years of related experience with a Bachelor’s degree; or 4 years and a Master’s degree; or 2 years with a PhD; or equivalent work experience.

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

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.