Staff Software Engineer (Perception)

Shield AI; Washington (Washington County); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Excellent Medical Coverage

Mental Health Employee Assistance Prog

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 a senior ML engineer to lead development of perception models for autonomous systems. You will design, train, and deploy state-of-the-art vision, vision-language, and vision-language-action models, building scalable data pipelines and robust evaluation loops.

You will collaborate with researchers, perception and autonomy engineers, and platform teams to bridge research with production, optimize models for embedded hardware, and mentor junior engineers as part of a

Qualifications

• 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.
• Experience training and deploying ML models for computer vision in a production setting.
• Proficiency in C++ and Python.
• Strong understanding of 3D vision problems/algorithms.
• Expertise of machine learning fundamentals.
• Experience with machine learning frameworks such as PyTorch and TensorFlow.
• 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.
• Experience with developing autonomous systems for defense customers.
• Track record of publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA).

Responsibilities

• Lead the technical development of advanced machine learning solutions that define the future of perception for autonomous systems.
• Own the team’s most challenging technical problems, drive architecture and model development across multiple efforts.
• Influence how foundation models are adapted, evaluated, and deployed for real-world autonomy.
• Bridge cutting-edge AI research with scalable production systems while mentoring engineers.
• 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, supervised fine-tuning (SFT) workflows, and evaluation loops.
• Model Deployment & Optimization – Deploy and optimize ML models for embedded hardware using ONNX, TensorRT, and hardware-accelerated inference frameworks.
• Perception & Autonomy Applications – Solve perception and autonomy problems across aerial and other autonomous systems.
• Research-to-Production – Translate research into production-ready capabilities balancing performance and reliability.
• Cross-functional Collaboration – Partner with perception, autonomy, platform, and software teams to integrate ML into mission-ready systems.
• Model Evaluation & Validation – Develop benchmarks, testing methodologies, and evaluation frameworks.
• Continuous Improvement – Improve training infrastructure, tooling, deployment workflows, and model lifecycle management.

Skills

C++

Python

TensorRT

ONNX

PyTorch

TensorFlow

3D Vision

Machine Learning Fundamentals

Vision-Language Models

Research to Production

Education

Bachelor's degree in a related field

Master's degree

PhD

Tools

ONNX

TensorRT

PyTorch

TensorFlow

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 lead the technical development of advanced machine learning solutions that define the future of perception for autonomous systems
• You’ll own the team’s most challenging technical problems, drive architecture and model development across multiple efforts, and influence how foundation models are adapted, evaluated, and deployed for real-world autonomy
• Working closely with researchers, perception engineers, autonomy engineers, and platform teams, you’ll bridge cutting-edge AI research with scalable production systems while mentoring engineers and raising the technical bar across the organization
• 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

Strong analytical and problem-solving skills, with the ability to translate research into practical applicationsDemonstrated expertise in deploying models using TensorRT and ONNXAbility to obtain a SECRET clearanceTypically 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 experienceExperience training an deploying ML models for computer vision in a production settingProficiency in C++ and PythonStrong understanding of 3D vision problems/algorithmsExpertise of machine learning fundamentalsExperience with machine learning frameworks such as PyTorch and TensorFlowExperience with training/finetuning vision-language models, vision-language-action models, and/or world modelsContributions to open-source projects in machine learning or computer visionExperience with developing autonomous systems for defense customersTrack record of publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA)