Staff ML & Physics Infrastructure Architect

Lila Sciences; Greater London; On-site; GBP 166,000 - 218,000; Full time

Benefits offered by this job

Equity

Bonus potential

Job summary

Lila Sciences is seeking a Staff Research Engineer to bridge research and production for ML/physics infrastructure. You will scale prototypes into robust, distributed systems across compute environments and collaborate with scientists to enable agent-usable workflows.

The role focuses on GPU efficiency, cluster portability, and reliable execution, with opportunities to shape workflows for drug discovery and scientific pipelines.

Qualifications

• Strong software engineering skills in Python and ML/scientific computing.
• Experience building or operating distributed systems for research/ML.
• Knowledge of GPU computing and performance profiling.
• Experience with PyTorch/JAX and CUDA workflows.
• Knowledge of Linux, Docker, dependencies, and reproducible environments.
• Experience with orchestration tools such as Kubernetes, Slurm, Ray, Flyte or Argo.
• Ability to turn prototype research code into scalable, reliable systems.

Responsibilities

• Scale research tools and workflows into scalable, maintainable systems.
• Collaborate with scientists to convert research workflows into agent-usable systems.
• Build and support ML and physics infrastructure for training and simulations.
• Ensure workflows run reliably across multiple clusters.
• Improve GPU utilization and fault tolerance for ML workloads.
• Architect larger-scale systems with job orchestration and monitoring.
• Optimize code for performance and scalability.
• Package tools as services or APIs for researchers.
• Bridge exploratory work with reliable engineering systems.
• Document systems and establish pragmatic engineering patterns.

Skills

Python

Distributed systems

GPU computing

PyTorch

JAX

Linux

Docker

Kubernetes

Debugging

Research collaboration

Tools

Docker

Kubernetes

Slurm

Ray

Flyte

Argo

CUDA

Job description

Lila Sciences is seeking a Staff Research Engineer to bridge research and production for ML/physics infrastructure. You will scale prototypes into robust, distributed systems across compute environments and collaborate with scientists to enable agent-usable workflows.

The role focuses on GPU efficiency, cluster portability, and reliable execution, with opportunities to shape workflows for drug discovery and scientific pipelines.