Senior ML Infrastructure Engineer

Do you want to build infrastructure that enables entirely new scientific discovery?

Have you scaled data systems for ML workloads where performance actually matters?

Are you ready to own foundational infrastructure at global, research-grade scale?

We’re working with a mission-driven AI research organisation applying advanced multimodal machine learning (audio, spatial, sensor, text, etc.) to understand animal communication. Operating at the intersection of ML research, large-scale data infrastructure, and real-world biological data, this team functions like a high-performance research lab with production-grade engineering standards.

They are entering a growth phase and are scaling the core systems that power distributed AI research, large multimodal datasets, and public-facing data platforms. This is not consumer tech or ad optimisation - the infrastructure you build directly enables new scientific discovery.

This is a Senior Infrastructure Engineer (Backend / Data Performance) position focused on designing, scaling, and hardening the data and backend platforms that support distributed ML workloads and TB–PB scale datasets. You’ll work closely with researchers and engineers to turn experimental systems into reliable, high-performance, production infrastructure.

• Design and optimise high-performance data pipelines for large, heterogeneous datasets
• Optimise distributed AI workloads for latency, throughput, reliability, and GPU utilisation
• Build observability tooling for data quality, pipeline health, and experiments
• Support GPU infrastructure for large-scale model training
• Translate research prototypes into robust, production systems
• Scope and supervise work for interns, PhDs, and post-docs
• Salary: up to £150k (may be flexibility to £160k) (UK)
• Working model: Fully remote (UK)
• Seniority: 5+ years backend / infrastructure engineering (flexible for exceptional profiles)