Our client is developing nexteneration AI systems designed to accelerate scientific discovery by addressing one of the biggest challenges in research and development: turning vast, complex data into actionable insights. Their mission is to enable scientists and enterprises to move faster, reduce risk, and make more confident decisions when developing critical innovations.

They are seeking a highly skilled Scientific Senior Software Engineer / Data Engineer to design and own the systems, pipelines, and infrastructure that transform raw chemical, biological, and clinical data into machine learning–ready training sets and actionable insights for enterprise users. The successful candidate will collaborate across AI, product, and scientific teams to build intelligent data platforms, scale image and graph neural networks, automate ETL from diverse and often messy sources, and ensure the reliability of datasets that drive decisions with real-world impact.

This role is ideal for someone who thrives on building clean, scalable systems that underpin mission-critical software and who wants their engineering craft to make a tangible difference in the scientific and healthcare space.

What our client is looking for

Our client is seeking engineers who raise the technical bar for everyone around them. They are looking for individuals with strong ownership mindset, sound engineering judgment, and the ability to operate across ambiguity and scale.

The ideal candidate could succeed in top-tier big tech or advanced AI companies, but actively chooses to work in a more technically challenging and mission-driven environment — where they can shape core infrastructure, define engineering standards, and contribute directly to the advancement of science through production-grade AI systems.

Responsibilities

• Architect and build the core distributed infrastructure that powers enterprise-scale scientific ML systems - spanning model training, evaluation, deployment, and real-world inference.
• Design and operate high-performance systems for ingestion, storage, retrieval, and transformation of chemical, biological, imaging, graph, and clinical datasets.
• Deploy cutting-edge LLMs and reasoning agents from research into secure, scalable, enterprise-ready production environments.
• Build fault-tolerant, automated ETL and feature-generation pipelines across structured, unstructured, image, and knowledge-graph data sources.
• Own ML system reliability including monitoring, evaluation pipelines, dataset and model versioning, performance tracking, and data quality guarantees.
• Partner deeply with AI researchers and scientists, mentoring them in production engineering best practices and helping translate research prototypes into robust, scalable platforms.
• Shape how the organisation evolves into a world-class engineering team delivering enterprise-grade AI software used in real scientific decision-making.

Experience that excites the client

• Built SaaS or data platforms at scale handling large, complex, and high-throughput datasets.
• Designed and delivered end-to-end production ML systems covering data pipelines, training, validation, deployment, and monitoring.
• Solved the hardest challenges in production ML reliability, including model drift, evaluation automation, data lineage, and observability.
• Built or scaled LLM-powered platforms for research automation, knowledge retrieval, or decision-support systems.
• Worked directly with enterprise customers, supporting large-scale technical deployments with real business and scientific consequences.

Key criteria

• Strong generalist software engineer with deep experience across:
• Backend systems
• Distributed systems
• Cloud infrastructure
• Data engineering
• Production machine learning platforms
• Proven record of owning and scaling mission-critical production systems used by demanding enterprise customers.
• Enjoys simplifying complex systems and building clean, elegant technical solutions.
• Actively invested in mentorship, team development, and engineering culture.
• Passionate about working alongside scientists and researchers to bridge deep science with world-class engineering.
• Obsessed with system reliability, technical ownership, and end-user experience.
• Relentlessly curious about both the underlying science and the real-world business impact of their work.
• If focusing on shipping awesome products to customers excites you, get in contact with julien.funes@aspirelifesciences.co.uk.

Explore how this opportunity aligns with your career goals. Apply today.

Please note that applicants must be legally authorised to work in the United States without the need for employer sponsorship, now or in the future.