Senior Staff Software Engineer (Perception)

Shield AI; Washington (Washington County); On-site; USD 140,000 - 220,000; Full time

Benefits offered by this job

Excellent Medical Coverage

Mental Health Employee Assistance Plan

Paid Parental Leave

Pet Insurance

Flexible Work Hours

Onsite Gym (DC)

Gym Discount (San Diego)

Free Parking

Competitive Compensation

Stock Benefits

401K Services and Match

Job summary

Shield AI is seeking engineers to develop state-of-the-art perception models and ML systems for autonomous platforms. You will design, train, and deploy vision-language models and related components to enable robust perception in real-world environments.

You will collaborate with researchers, autonomy, perception, and platform teams to translate research into reliable, production-ready capabilities for defense customers, while optimizing deployment on embedded hardware.

Qualifications

• Typically requires a minimum of 10 years of related experience with a Bachelor’s degree, or 9 years with a Master’s, or 7 years with a PhD.
• Proficiency in C++ and Python for production systems.
• Experience deploying ML models for computer vision in production.
• Strong analytical and problem-solving skills; translate research into practical applications.
• Track record of publications in CV/robotics venues.

Responsibilities

• Design, train, fine-tune, and maintain state-of-the-art vision, vision-language, and vision-language-action models.
• Build scalable data pipelines and evaluation loops for mission-relevant tasks.
• Deploy and optimize ML models for embedded hardware using TensorRT and ONNX.
• Collaborate with researchers, autonomy, perception, and platform teams to deliver production-ready systems.
• Ensure systems meet reliability, robustness, and security requirements for defense customers.

Skills

C++

Python

ML frameworks

PyTorch

TensorFlow

TensorRT

ONNX

3D vision

autonomy systems

defense customers

Education

Bachelor’s degree

Master’s degree

PhD

Tools

PyTorch

TensorFlow

ONNX

TensorRT

Job description

• 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
• 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

Benefits

• Excellent Medical Coverage
• Mental Health Employee Assistance Program
• Paid Parental Leave
• Pet Insurance
• Flexible Work Hours
• Onsite Gym (DC)
• Gym Discount (San Diego)
• Free Parking
• Competitive Compensation
• Stock Benefits
• 401K Services and Match

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 experienceStrong analytical and problem-solving skills, with the ability to translate research into practical applicationsProficiency in C++ and PythonAbility to obtain a SECRET clearanceExperience with machine learning frameworks such as PyTorch and TensorFlowExperience training an deploying ML models for computer vision in a production settingStrong understanding of 3D vision problems/algorithmsMastery of machine learning fundamentalsDemonstrated expertise in deploying models using TensorRT and ONNXExperience with developing autonomous systems for defense customersContributions to open-source projects in machine learning or computer visionExperience with training/finetuning vision-language models, vision-language-action models, and/or world modelsTrack record of publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA)