Python Expert

Role overview

AI-to-production engineering

• Refactor AI-team Python code into clean, modular, production-grade architecture.
• Optimize inference scripts for edge-device memory and speed constraints across local vision models and ANPR pipelines.
• Use asynchronous programming, multithreading, and multiprocessing to process concurrent video streams and trigger hardware events.

API development and data routing

• Design, build, and maintain high-performance microservices and RESTful APIs, primarily with FastAPI, to serve computer-vision models.
• Build data handoff layers between Python AI edge systems and the Node.js, Redis, and SQL backend.
• Securely and reliably transmit camera event data, images, and system-health metrics over VPN tunnels such as WireGuard to central databases.

Integration and support

• Work with the AI team to understand new model architectures before deployment.
• Integrate Python microservices into infrastructure and CI/CD deployment pipelines with the Backend Engineer and System Administrator.
• Troubleshoot latency, network bottlenecks, and integration bugs between edge processing and server-side logic.

Technical qualifications

• At least 4 years of advanced software engineering experience focused on Python in production environments.
• Expert proficiency in FastAPI or a similar asynchronous web framework, plus deep understanding of Python memory management and concurrency.
• Practical experience wrapping and deploying computer-vision models such as YOLO, OpenCV, or PyTorch/TensorFlow runtimes; model training is not required.
• Strong understanding of distributed systems, message brokers or caching such as Redis, and integration with Node.js backends.
• Hands-on Docker experience and deployment in edge-computing or IoT environments.

Preferred skills

• C++ or Python integration with C/C++ extensions is listed as preferred in the skills section, while the experience section also states 4 years as required.
• Smart-city infrastructure, intelligent transportation systems, or physical camera/IoT network experience is preferred.
• Hardware acceleration knowledge, including NVIDIA TensorRT and CUDA, is listed as preferred in the skills section, while the experience section also states 4 years as required.

Application note

• The posting includes an immediate-joining question.