HUG are currently partnered with a well-funded, high-growth AI startup building advanced machine learning systems deployed in real-world production environments. They are hiring a Senior ML Systems Engineer to build and scale the infrastructure that enables cutting-edge ML models to move from research into production.
The Role
* This is a highly technical IC engineering role sitting at the intersection of ML systems, infrastructure, and large-scale data.
* You will be responsible for building the platforms and systems that allow applied scientists to train, evaluate, and deploy models efficiently at scale.
* This role is not research-focused, it is about making ML systems work reliably in production. You’ll operate across the full lifecycle, from data ingestion through to inference and optimisation.
What You’ll Be Doing
* Build and scale data platforms for large, complex datasets
* Improve ML training infrastructure and data pipelines
* Develop tooling for dataset inspection, model evaluation, and experimentation
* Design systems for model versioning, lifecycle management, and deployment
* Optimise production inference pipelines and system performance across distributed/GPU environments
* Work closely with researchers to enable rapid experimentation and productionisation
What They’re Looking For
* 5+ years experience building production ML systems or ML infrastructure
* Experience deploying ML models at scale or building platforms/tools for ML teams
* Strong Python experience
* Experience with a production language (e.g. C++, Java, Scala)
* Solid understanding of distributed systems
* Experience working with large-scale, high-volume datasets
* Experience in a startup or scale-up environment (ideally 50–300 people)
* Product-minded, able to balance technical depth with real-world impact
Nice to Have
* Experience with modern ML tooling (e.g. PyTorch, Ray, Triton, Spark, Iceberg)
* Background working with complex or non-standard data types
* Experience optimising performance across distributed or GPU systems
* Exposure to ML platform tooling for research teams
Logistics
* London (hybrid)
* £100k-£155k base + equity
* Visa sponsorship available