Senior Software Engineer (Perception)

Shield AI; Ashington; On-site; GBP 75,000 - 120,000; Full time

Benefits offered by this job

Medical coverage

Parental leave

Stock benefits

401K matching

Flexible work hours

Onsite gym

Job summary

Shield AI is seeking engineers to develop and deploy state-of-the-art perception models for autonomous systems. You will own features from model development through deployment, collaborating with researchers, perception engineers, autonomy engineers, and platform teams to bring cutting-edge AI capabilities into production.

You will work on vision, vision-language, and vision-language-action models, building data pipelines, SFT workflows, and optimization for embedded hardware using ONNX,

Qualifications

• Experience training and deploying ML models for computer vision in production.
• Proficiency with PyTorch and TensorFlow.
• Deploy models using TensorRT and ONNX.
• Strong C++ and Python programming skills.

Responsibilities

• Develop and deploy advanced ML models for perception in autonomous systems.
• Own major features from development through deployment.
• Collaborate with researchers, engineers and platform teams.
• Build scalable data pipelines and evaluation loops.

Skills

Python

C++

PyTorch

TensorFlow

TensorRT

ONNX

3D vision

Research to production

Education

Bachelor's degree

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 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

Experience training an deploying ML models for computer vision in a production settingPrioficiency of machine learning fundamentalsExperience with machine learning frameworks such as PyTorch and TensorFlowDemonstrated expertise in deploying models using TensorRT and ONNXProficiency in C++ and PythonStrong analytical and problem-solving skills, with the ability to translate research into practical applicationsStrong understanding of 3D vision problems/algorithmsTypically 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 experienceAbility to obtain a SECRET clearanceExperience 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)