🚀 Senior / Staff ML Systems Engineer
đź“Ť London (Hybrid)
đź’° Up to ÂŁ150k
🏢 Well-funded AI company (£100m+ raised)
We’re working with a fast-growing AI company building production systems for training and deploying cutting-edge multimodal models across video, embeddings, and large-scale metadata.
You’ll join a small, highly technical team owning the ML infrastructure and systems layer end-to-end — from large-scale data ingestion and training pipelines through to high-performance production inference.
What you’ll be doing 👇
• Building and scaling infrastructure for massive multimodal datasets
• Improving distributed ML training systems using PyTorch and Ray
• Developing tooling for experimentation, evaluation, and dataset analysis
• Owning model lifecycle workflows across training, deployment, and rollout
• Optimising GPU inference systems for performance, latency, and reliability
What they’re looking for đź§
• Strong background in ML systems engineering or production ML infrastructure
• Experience deploying ML models into real-world production environments
• Strong Python skills plus experience with a systems language (C++ / Java etc.)
• Experience working with distributed systems and large-scale datasets
• Engineers who enjoy solving practical problems end-to-end rather than purely research work
Tech ⚙️
• Python, PyTorch, Ray
• Distributed systems & GPU infrastructure
• Large-scale data platforms
• ML serving & inference systems
Why it’s interesting 💡
• Real-world AI systems operating at significant scale
• High ownership within a small, senior engineering team
• Direct collaboration with applied scientists and research teams
• Strong commercial traction and significant backing
• Opportunity to help shape the next stage of platform growth