Our client is developing next-generation 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

The client seeks engineers who raise the bar for everyone around them—people with high energy, strong initiative, and a sharp sense of priorities. Candidates should be able to see problems clearly, decide quickly, and execute relentlessly.

The ideal candidate might thrive in big tech but chooses to work in a more challenging, meaningful, and rewarding environment: pushing the frontier of AI and science while shaping an engineering culture that inspires curiosity, discipline, and collaboration.

Responsibilities

• Architect and build the infrastructure that powers large-scale scientific ML systems, from model evaluation and deployment to customer-facing data platforms.
• Design robust systems for inference, storage, and retrieval of chemical, biological, and clinical datasets.
• Deploy cutting-edge reasoning agents from research into production, integrating them into enterprise-grade environments.
• Automate and scale ETL workflows to handle data across literature, images, graphs, and structured sources.
• Collaborate with researchers and scientists, mentoring them in engineering best practices and helping them become stronger technical contributors.
• Shape the evolution of the company into a world-class engineering organization delivering enterprise-grade AI software.

Experience that excites the client

• Built SaaS products handling large, complex datasets at scale.
• Designed and delivered enterprise ML systems covering data pipelines, training, evaluation, and deployment.
• Tackled the hard aspects of production ML - monitoring, versioning, evaluation pipelines, and reliability at scale.
• Created or scaled LLM-powered data systems, particularly for research, knowledge retrieval, or decision support.
• Worked directly with enterprise customers to support and scale complex technical needs.

Key criteria

• Strong generalist software engineer with experience in cloud infrastructure, machine learning, backend, and distributed systems.
• Proven track record of deploying production systems used by enterprise customers.
• Enjoys simplifying complex problems and building elegant solutions.
• Invested in team growth and fostering a strong engineering culture.
• Passionate about working alongside researchers and scientists to bridge the gap between deep science and great engineering.
• Obsessed with reliability, ownership, and the customer experience.
• Relentlessly curious about both the underlying science and the 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, applicants must be legally authorised to work in the United States without the need for employer sponsorship, now or in the future.