Staff AI Systems Engineer for Drug Discovery

Sponsor Finder; Boston; On-site; GBP 90,000 - 130,000; Full time

Job summary

Proxima seeks a Member of Technical Staff to own the systems behind its drug discovery research. You will work across data pipelines, model training and evaluation, inference, and compute infrastructure, delivering reliable scientific workflows and scalable tooling.

The role requires deep Python skills, PyTorch expertise, and experience with Linux, containers, Kubernetes, and cloud storage. You will collaborate with researchers to deploy robust solutions that accelerate discovery.

Qualifications

• Experience owning large software systems from design to deployment.
• Experience building ML or scientific computing workflows.
• Practical PyTorch experience, including memory management and device placement for training and inference.
• Ability to learn unfamiliar systems and make independent, data-driven decisions.

Responsibilities

• Build reliable scientific workflows that colleagues can run, reproduce, and troubleshoot with less manual intervention.
• Integrate models, datasets, and evaluation methods while preserving scientific validity and data correctness.
• Improve the performance, cost, and reliability of shared compute through better scheduling, monitoring, and fault recovery.
• Identify and remove bottlenecks in data preparation, execution, and evaluation to speed up research cycles.
• Build and maintain APIs, libraries, and automation to reduce manual work and accelerate research.
• Identify engineering gaps that constrain progress and demonstrate the impact of your solutions.

Skills

Python

PyTorch

Linux

Containers

Kubernetes

CI/CD

ML workflows

Data pipelines

Tools

Docker

Cloud platforms

CI/CD tools

Job description

Proxima seeks a Member of Technical Staff to own the systems behind its drug discovery research. You will work across data pipelines, model training and evaluation, inference, and compute infrastructure, delivering reliable scientific workflows and scalable tooling.

The role requires deep Python skills, PyTorch expertise, and experience with Linux, containers, Kubernetes, and cloud storage. You will collaborate with researchers to deploy robust solutions that accelerate discovery.