Senior Software Engineer (Perception)

Shield AI; Washington (Washington County); On-site; USD 120,000 - 190,000; Full time

Job summary

Shield AI is seeking an experienced ML/vision engineer to develop and deploy state-of-the-art perception models for autonomous platforms. You will design, train, and fine-tune vision, vision-language, and vision-language-action models, building end-to-end data pipelines and evaluation loops for production use.

You will collaborate with researchers and engineers to deploy models on embedded hardware, balance performance and reliability, and support defense-related autonomous systems in complex

Qualifications

• Proficiency in C++ and Python.
• Experience with PyTorch and TensorFlow.
• Deploying models using TensorRT and ONNX.
• Experience training and deploying ML models for computer vision in production.
• Strong fundamentals in machine learning.

Responsibilities

• Design, train, fine-tune, and maintain state-of-the-art vision and vision-language models for autonomous systems.
• Build scalable data pipelines and supervised fine-tuning workflows.
• Deploy and optimize ML models for embedded hardware using ONNX, TensorRT.
• Collaborate with researchers, perception engineers, autonomy engineers, and platform teams.
• Evaluate models with benchmarks, identify failure modes, and guide improvements.

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 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

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

• Proficiency in C++ and PythonStrong analytical and problem-solving skills, with the ability to translate research into practical applicationsExperience with machine learning frameworks such as PyTorch and TensorFlowDemonstrated expertise in deploying models using TensorRT and ONNXExperience training an deploying ML models for computer vision in a production settingPrioficiency of machine learning fundamentalsAbility to obtain a SECRET clearanceTypically 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 experienceStrong understanding of 3D vision problems/algorithmsExperience with developing autonomous systems for defense customersExperience with training/finetuning vision-language models, vision-language-action models, and/or world modelsContributions to open-source projects in machine learning or computer visionTrack record of publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA)