Senior Software Engineer | Python | Backend | React | Frontend | AWS | London

About the company

We are an early-stage technology company focused on accelerating the development of more productive, sustainable, nutritious, and climate-resilient food sources. Our work centres on building an ML-driven target discovery platform to support crop gene-editing.

While crop gene-editing technologies are advancing rapidly, identifying which genes to edit — and why — remains a major bottleneck. We apply modern machine learning techniques to identify high-value genetic targets for crop improvement. Our approach draws inspiration from advances in drug discovery, incorporating transformers, graph-based methods, and causal ML to support plant science research.

Over the past two years, we have built strong ML and bioinformatics foundations for gene discovery, including curated plant datasets, reproducible pipelines, and bespoke models. The next phase is to turn these foundations into a unified, agent-native product that scientists can use end-to-end: from trait specification and data curation, through target generation and deep-dive analysis, to producing defensible evidence packs. This role sits at the centre of that transition.

Team

We are a small, interdisciplinary team spanning machine learning, data engineering, bioinformatics, and experimental science. The team works closely together, with a strong emphasis on collaboration across technical and scientific disciplines. This role will be based in a shared office environment, with regular in-person collaboration.

The role

We are hiring a full-stack software engineer to build the internal discovery product that ties together workflows developed and optimised over the last two years. You will translate real scientific practice into software by designing canonical product objects (e.g. project specifications, curated datasets, long-lists, evidence cards), implementing “scientist-in-the-loop” interfaces, and integrating in-house models, bioinformatics tooling, and agent workflows into a cohesive experience.

Initial priorities

• Build the core product objects and minimal UX/UI that anchor discovery projects
• Turn internal data-curation tooling into a comprehensive workbench, connected to curated and quality-controlled dataset objects and onboarding workflows
• Ship a usable internal target-identification workflow that supports a near-term enterprise discovery project, while remaining aligned with longer-term internal discovery needs

Core responsibilities

• Build and iterate on internal product UX for:
• Trait and project specification
• Dataset curation
• Interactive target selection
• Per-target evidence cards and review flows
• Integrate existing scientific tooling (ML models, bioinformatics pipelines, etc.) into a unified workflow
• Work with data and engineering teams to design and implement canonical data models representing discovery work, with strong provenance and versioning
• Collaborate closely with scientific leads to ensure workflows reflect real discovery practices and minimise context switching for scientists
• Support customer-facing deliverables by ensuring outputs are easy to review, export, and defend

Additional responsibilities

• Work with leadership and internal product stakeholders to translate requirements into a roadmap for a unified discovery platform
• Improve developer and scientist experience around debugging, reviewing, and reproducing discovery runs
• Contribute to engineering standards for scientific traceability and human-in-the-loop checkpoints

Core competencies

• Strong full-stack or backend engineering background, with a bias toward building clean, reliable internal tools
• Experience designing data models and schemas and building product surfaces on top of them
• Comfort operating in ambiguous product spaces and iterating quickly with end users
• Ability to bridge disciplines: working effectively with scientists and ML engineers to translate workflow pain points into software
• Solid Python skills; familiarity with modern web stacks (e.g. React/TypeScript) or willingness to work across the stack
• Strong attention to correctness, provenance, and reproducibility in systems that generate scientific claims

Nice-to-have competencies

• Experience building tools for scientists, biotech teams, or other high-integrity domains
• Familiarity with workflow or data orchestration tools, model registries, or agent frameworks
• Experience with knowledge-graph, evidence-graph, or structured reporting products
• Interest in plant biology, gene regulation, or crop improvement (not required)

Benefits

• Competitive salary and equity options
• Generous annual leave and flexible work-location policy
• Comprehensive benefits package
• Career development opportunities as the company scales
• Ownership of ambitious, mission-driven work with real-world impact
• Supportive, collaborative team environment
• Access to conferences, events, and professional development resources

Senior Software Engineer | Python | Backend | React | Frontend | AWS | London