_{16th April, 2026}

Senior Systems Engineer | Real-Time Video AI Infrastructure
  
Our client is a specialised technology company building a platform that uses AI to run production-grade machine learning models on massive, real-time video data streams.
  
The platform lets users define events, harvest data, trigger instant incident detection, send alerts, and archive footage, all happening concurrently at scale. It is used in high-stakes security and defence environments where low-latency, reliable performance is non-negotiable.
  
We are looking for a strong Systems Engineer to join a small, high-performing Machine Learning team. You will focus on the software systems layer of the product, not core ML research, but the critical infrastructure that makes the AI run fast, securely, and at scale in production. This is a hands-on role building and optimising the real-time video processing and inference systems that power the entire platform.
  
Senior Systems Engineer Responsibilities

• Design, build and optimise low-latency video processing pipelines and inference systems handling high-bandwidth real-time streams.
• Own the end-to-end systems that deploy and run production ML models on live video data.
• Perform R&D to push the platform forward, including extending GStreamer elements and creating high-performance Rust bindings for C/C++ libraries.
• Continuously improve speed, latency, throughput and resource efficiency of the core video and inference stack.
• Work closely with ML engineers to productionise new capabilities while maintaining rock-solid system performance.

Senior Systems Engineer Requirements

• Strong Systems Engineering experience with a proven track record in low-latency, high-bandwidth environments (video processing, real-time data pipelines, or similar high-performance systems).
• Hands-on work with video codecs, inference engines, streaming pipelines or related low-level technologies.
• Deep comfort operating at the systems level, profiling, optimising and troubleshooting performance-critical code.
• Rust experience is highly preferred, but not essential. They actively support rapid onboarding with AI coding tools and expect you to become productive in Rust quickly.

If you’re interested in learning more, please apply with your most up-to-date resume & I’ll be in touch!

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