Staff Backend Engineer (AI Lab | £170,000)
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Role: Staff Software Engineer (Python | Backend | Infrastructure)
Location: Hybrid - 2-3 days in London Office
Compensation: Up to £170,000 + equity
We’re working with a frontier AI lab pushing the boundaries of computational biology, combining machine learning, cloud infrastructure, and scientific research to accelerate discoveries in life sciences.
As a Staff Backend Engineer , you’ll build the distributed systems and data infrastructure that power the lab’s next-generation biology platform. From model serving to real-time data processing, your work will form the backbone of a platform enabling scientists to explore and manipulate biological data in entirely new ways.
What you’ll do
- Design and own backend architecture for large-scale, data-intensive applications.
- Develop and optimize APIs that handle complex biological and ML-driven workloads.
- Build and maintain data pipelines for ingesting, transforming, and serving scientific data at scale.
- Deploy and manage infrastructure across Kubernetes and AWS, ensuring robustness and observability.
- Drive system reliability through automated testing, monitoring, and fault-tolerant design.
- Collaborate across disciplines , working with ML engineers, biologists, and platform teams to ensure seamless integration between computation, data, and science.
You should have
- Deep experience building and scaling backend systems and distributed applications .
- Strong coding skills in Python , with an understanding of performance tuning and concurrency.
- Hands-on experience with Kubernetes , AWS , and modern cloud infrastructure .
- Proficiency with databases — schema design, performance optimization, and analytics.
- Familiarity with REST APIs , websockets, and authentication/security best practices.
- A disciplined engineering mindset — you think about reliability, maintainability, and long-term scalability.
Nice-to-haves
- Experience with MLOps and model-serving infrastructure.
- Background in high-performance computing or large-scale scientific workloads.
- Expertise in data pipeline architecture and real-time streaming systems.
- Knowledge of scientific or biological computing environments .
This is a rare opportunity to join a deep-tech AI lab where backend engineering meets scientific discovery, building the systems that let machine learning models and experimental biology evolve together.
If you want to design the infrastructure behind a platform that could change how we understand life itself, we’d love to hear from you.
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