[Hiring] OT Artificial Intelligence Computer Vision Engineer @S3 Int

Role Description

We are seeking an OT Artificial Intelligence Computer Vision Engineer to design, develop, deploy and operate production-grade vision solutions for industrial environments. This role turns images, video and operational context into dependable capabilities for:

• Inspection
• Safety monitoring
• Asset condition assessment
• Anomaly detection
• Remote operations
• Robotics and autonomous systems

This position is part of an industrial AI team and provides hands-on computer vision engineering leadership and delivery support for operational technology (OT) AI use cases. The role builds reusable approaches for:

• Visual data acquisition
• Annotation
• Model development
• Validation
• Optimization
• Deployment
• Monitoring across fixed cameras, mobile devices, drones, robots, edge systems and approved cloud environments

The team is highly technical, creative and cross-functional. The Computer Vision Engineer will work with:

• Industrial domain experts
• Data engineers
• Machine learning engineers
• Solution architects
• Cybersecurity teams
• Operations personnel

Success means delivering measurable outcomes while ensuring performance remains dependable across changing conditions.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, Artificial Intelligence or a related field, or equivalent experience.
• Five or more years of experience developing and deploying production computer vision or machine learning solutions.
• Strong programming skills in Python and experience with production software engineering, testing, source control, code review and CI/CD.
• Hands-on experience with computer vision and deep learning frameworks such as OpenCV, PyTorch, TensorFlow or equivalent technologies.
• Experience with object detection, classification, segmentation, tracking, image preprocessing, augmentation, evaluation and error analysis.
• Experience preparing and governing image or video datasets, including collection, annotation, quality review, ground truth, lineage and versioning.
• Experience deploying and monitoring vision models using containers, APIs, model registries, orchestration and automated delivery pipelines.
• Experience evaluating camera placement, field of view, resolution, frame rate, lighting and environmental factors that affect model performance.
• Understanding of OT cybersecurity, network segmentation, least-privilege access and the constraints of industrial environments.
• Ability to communicate vision-system behavior, uncertainty, limitations and operational risk to engineers, operators, architects, cybersecurity reviewers and business stakeholders.
• Demonstrated ownership of production vision services, including troubleshooting, incident response, documentation and continuous improvement.

Requirements

• Master's degree in Computer Science, Computer Vision, Robotics, Artificial Intelligence or a related field (preferred).
• Experience with Microsoft Azure AI services, Azure Machine Learning, Azure AI Vision or equivalent platforms (preferred).
• Experience delivering industrial inspection, leak detection, corrosion, flame or flare monitoring, PPE, perimeter, equipment-state or safety-related vision use cases (preferred).
• Experience with thermal, infrared, multispectral, depth, stereo or other specialized imaging modalities (preferred).
• Experience integrating cameras and vision workloads with drones, robots, fixed inspection systems or autonomous platforms (preferred).
• Experience deploying optimized edge inference using GPUs, NPUs or other AI accelerators in constrained or intermittently connected settings (preferred).
• Experience with model compression, quantization, pruning, distillation, ONNX, TensorRT or hardware-aware optimization (preferred).
• Experience with video analytics, multi-camera tracking, three-dimensional vision, visual localization, photogrammetry or sensor fusion (preferred).
• Experience with responsible AI, privacy-preserving vision, explainability, adversarial testing or AI assurance (preferred).
• Experience in industrial environments, including energy, manufacturing or other asset-intensive industries (preferred).

Critical Selection Criteria

• Computer Vision Capability: Demonstrated ability to design, train, validate, deploy and sustain production vision models and end-to-end imaging solutions using disciplined software engineering and MLOps practices.
• Field Performance: Ability to account for cameras, lighting, weather, motion, occlusion, viewpoint, background and operational variability, and to implement effective monitoring, human review, fallback and rollback mechanisms.
• OT and AI Understanding: Knowledge of industrial operations, visual inspection workflows, OT cybersecurity and the lifecycle required to move vision solutions from experimentation into dependable field use.
• Collaboration and Communication: Ability to translate operational problems into measurable computer vision objectives and clearly explain performance, uncertainty, false-alarm trade-offs, limitations and risks to technical and nontechnical stakeholders.