Posted: 11h ago
The role
Job Description
Our client is an innovative start-up operating at the cutting edge of industrial biotechnology, combining artificial intelligence, computational modelling, robotics, laboratory automation, and advanced data infrastructure to accelerate the development of high-performance enzymes through biocatalysis.
At the heart of the business is a proprietary closed-loop enzyme optimisation platform that integrates AI-guided protein engineering, high-throughput robotics, experimental validation, structured scientific databases, and iterative machine learning — enabling continuous improvement of enzyme performance in real-world industrial settings.
With a bold vision for the future of industrial biotechnology, this organisation is building toward autonomous scientific systems where AI, robotics, software, and experimental science operate together in tightly integrated learning loops.
This is a deeply hands-on role for an ambitious engineer who wants to work on real-world AI systems operating at the intersection of machine learning, robotics, scientific experimentation, and industrial biotechnology.
Responsibilities
- Design, build, and scale AI-powered software, machine learning infrastructure, and scientific data platforms
- Develop pipelines for biological, experimental, and robotics-generated datasets
- Build and deploy AI models and automation tools that accelerate scientific workflows and decision-making
- Help architect a closed-loop AI, robotics, and data platform
- Work closely with scientists and automation engineers to integrate AI with laboratory robotics and experimental workflows
- Rapidly prototype and deploy AI-enabled systems using modern engineering practices
- Use AI development tools and coding assistants to maximise development speed
- Contribute to scientific database architecture and scalable data infrastructure
- Solve complex problems across machine learning, data systems, and scientific computing
- Participate in technical planning and architecture discussions as the business scales
- Collaborate across AI, software, robotics, and science teams to build integrated systems
- Support and mentor junior engineers as the team grows
Required Experience
- Experience building AI systems in biotech, scientific computing, robotics, or other deep-tech environments
- Experience working with noisy, sparse, or highly specialised datasets
- Experience using AI-assisted development tools or automated engineering workflows
- Experience with cloud infrastructure, MLOps, distributed systems, or scalable AI platforms
- Familiarity with laboratory automation, robotics platforms, or closed-loop experimentation
- Experience in fast-moving startup or scale-up environments
- Experience mentoring engineers or contributing to technical leadership
- Interest in computational biology, protein engineering, or scientific AI systems
