Senior Full Stack Engineer
About the Company
We are an ambitious, research-led technology company using advanced machine learning to tackle complex scientific and real-world challenges.
Our interdisciplinary team brings together expertise in machine learning, software engineering, and scientific research. We are building technology that turns frontier generative models into reliable production systems that researchers and external partners can use effectively.
We’re looking for a Senior Full Stack Engineer to help build the software and infrastructure connecting cutting-edge research with real-world applications.
Performance Objectives
- Ship production-grade APIs, services, and user interfaces that serve proprietary generative models reliably, enabling researchers and partners to run inference against complex scientific targets.
- Build and scale data pipelines that ingest experimental results, construct training and evaluation datasets, and feed outcomes back into machine-learning workflows.
- Own end-to-end features from prototype through production, delivering robust, tested, and maintainable code within a shared research and engineering codebase.
- Build systems supporting model training and inference using cloud-based accelerated computing infrastructure.
- Design effective benchmarks, monitoring, and observability so model performance, latency, reliability, and cost are visible to technical and non-technical stakeholders.
- Partner closely with machine-learning researchers, scientists, and other domain experts to translate real-world constraints into effective software systems.
- Help raise engineering standards across CI/CD, code review, infrastructure, testing, and development practices, enabling a small interdisciplinary team to move quickly without compromising quality.
Environment & Resources
You’ll join a growing, venture-backed technology company with teams in the UK and US.
The role sits within the engineering function and involves close collaboration with machine-learning researchers and scientific specialists. You’ll work within a shared codebase and have access to modern cloud infrastructure, accelerated computing resources, version-control tooling, and scientific data systems.
The company operates a hybrid working model and offers a competitive compensation package alongside benefits including healthcare, retirement contributions, generous leave, parental leave, and opportunities for team travel.
Essential Qualifications
- Proven experience delivering production full-stack systems, including APIs, data pipelines, and front-end applications, with ownership from conception through deployment.
- Strong software engineering fundamentals, including writing robust, tested, reviewed, and maintainable code.
- Ability to prototype rapidly while maintaining appropriate production-quality engineering standards.
- Experience with cloud-based model training and inference, distributed systems, data infrastructure, or similar computational workloads.
- Experience building performant data pipelines and production systems that interact with large machine-learning models.
- Ability to thrive in a fast-moving and sometimes ambiguous research or deep-tech environment.
- Strong collaboration skills and an ability to work effectively across engineering, machine learning, scientific research, and product disciplines.
- Intellectual curiosity and a willingness to develop sufficient domain knowledge to make informed technical and product decisions.
Role Selling Points
- Work alongside highly experienced researchers, engineers, and scientists on technically challenging problems at the frontier of machine learning.
- Build production software that directly connects advanced generative models with real-world scientific research and experimentation.
- Join an interdisciplinary culture that values scientific excellence, engineering quality, and rapid iteration.
- Help shape the architecture, engineering practices, and technology platform of a young company as it scales.
- Hybrid working, a competitive compensation package, and a team that values diverse backgrounds and continuous learning.
If you’re excited about building the software layer that turns frontier machine-learning research into useful real-world systems, we’d love to hear from you.

We welcome applicants from a wide range of backgrounds and experiences.