Senior Technical Software Engineer - AI Computer Vision

Role overview

Responsibilities

• Assess computer vision and AI initiatives with business and technical stakeholders and define feasible solutions for contactless passenger experiences.
• Own solutions end to end, including architecture, model selection, development, testing, and deployment across airport environments.
• Design and optimize GPU-accelerated multi-camera vision, video analytics, and inference pipelines for high-volume video streams.
• Apply computer vision, AI, and NVIDIA technologies to passenger experience, efficiency, security, and automation opportunities.
• Troubleshoot model accuracy, camera configuration, video processing, GPU performance, integration, and production reliability.
• Integrate solutions into the airport technology ecosystem while meeting operational and security requirements.
• Mentor engineering teams; establish practices for development, benchmarking, deployment, monitoring, and continuous improvement.
• Promote lean development, built-in quality, test-driven development, Agile practices, root cause analysis, and blameless post-mortems.
• Contribute expertise to work planning and technology communities of practice; use approved enterprise platforms and support product maintenance.

Qualifications

• Degree or honours in Computer Science, Computational Mathematics, Computer Engineering, Software Engineering, or a related field.
• At least 5 years in computer vision, machine learning, or AI engineering delivering large-scale, secure solutions, including GPU inference and video analytics, in enterprise Agile environments.
• Hands-on multi-camera computer vision experience covering detection, recognition, tracking, Re-ID, 3D or multi-view vision, and the full model lifecycle.
• Experience building enterprise AI solutions with DevOps, edge/cloud deployment, AI-assisted development tools, and responsible AI practices.
• Technical leadership and mentoring experience, stakeholder collaboration, problem-solving, risk management, incident management, production support, and root cause analysis.

Technical knowledge

• Software engineering: microservices; Python, C++, NodeJS, and Java; algorithms, data structures, concurrency, performance engineering, and integration tools such as Solace.
• Computer vision and video: detection, recognition, tracking, Re-ID, scene understanding, multi-camera/multi-view 3D vision, camera calibration, spatial mapping, RTSP/IP cameras, and GStreamer.
• AI/ML: PyTorch, OpenCV, ONNX Runtime, dataset curation and annotation, training and fine-tuning, Vision Foundation Models, VLMs, generative AI, and edge AI.
• NVIDIA/GPU: MV3DT, DeepStream SDK, TAO Toolkit, TensorRT, CUDA, GPU inference, FP16/INT8, Omniverse/Isaac Sim, and USD.
• Data and deployment: relational/NoSQL databases, CI/CD, observability, AWS/Azure/Google Cloud, Docker, Kafka, and edge-to-cloud deployment.
• Secure data handling across collection, training, and deployment in sensitive environments.

Benefits

• The posting describes a tax-free salary and industry travel benefits, including flight and hotel discounts.