Software Engineer (Machine Learning)

• Reports to: Amy Strange
• We are recruiting for a knowledgeable Machine Learning Engineer to join the Software Engineering and AI team at the Francis Crick Institute
• Working closely with researchers and technical specialists, you will help develop innovative machine learning solutions that accelerate scientific discovery, while also contributing to the development and support of institute wide applications and services
• As part of a collaborative team of engineers, you will apply your expertise to design, implement and deploy solutions to complex biological challenges and play a key role in supporting and advancing world leading scientific research
• Design and develop high-quality, maintainable software to meet project needs and deadlines (including the interpretation of project requirements and technical specifications across multiple research and operational domains)
• Collaborate effectively with internal scientists and core facilities as well as external partners, building solid working relationships across the institute and beyond
• Collaborate within the team through peer review and co-development, maintaining quality standards
• Assist in the planning of projects by assessing feasibility, prototyping, and providing time and resource estimates
• Take a project through its lifecycle, through user engagement, scoping, prototyping, planning, delivery, and maintenance
• Stay current in the field, and share knowledge/ideas across the team

Benefits

• 28 days of holiday each year, plus three additional days (usually taken over Christmas) and bank holidays
• Life assurance
• Season ticket/car parking loan
• Annual leave purchase
• Childcare support allowance
• Back-up dependent care
• Discounted annual gym membership
• Bike to Work scheme
• Payroll giving
• Shopping discounts
• Defined contribution pension scheme, with the Crick contributing between 3% - 16% of salary

An understanding of reproducibility, repeatability and replicability for scientific software and experience of building and distributing reproducible softwareExperience with LLM/agentic frameworks (such as LangChain, LlamaIndex, DeerFlow, Haystack, or others)*Evidence of understanding good software engineering practiceExperience developing and evaluating agents, skills, tools, or MCPs*Experience running code on high-performance computing clusters (or equivalent cloud environment)Excellent communication skills, with the ability to build effective relationships at all levels and the ability to communicate technical concepts to a non-technical audience*Strong software engineering fundamentals in Python*Experience with containerised environments (Docker, Apptainer etc.)*Excellent understanding of machine learning theory and related mathematical principles

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