Software Engineer (Machine Learning)

Francis Crick; Greater London; On-site; GBP 70,000 - 95,000; Full time

Benefits offered by this job

28 days annual leave

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

Job summary

Francis Crick Institute in London is seeking a Machine Learning Engineer to join the Software Engineering and AI team. You will design and deploy ML solutions that accelerate scientific discovery while contributing to institute-wide applications and services.

Working with researchers and technical specialists, you will develop software to tackle complex biological challenges, plan projects with feasibility assessments, and maintain quality through peer reviews and collaboration.

Qualifications

• Experience with reproducible scientific software and reproducibility concepts.
• Experience with LLM/agentic frameworks (LangChain, LlamaIndex, DeerFlow, Haystack, or others).
• Evidence of good software engineering practices.
• Experience developing and evaluating agents, tools, or MCPs.
• Experience running code on HPC clusters or cloud environments.
• Excellent communication skills for cross-disciplinary work.
• Strong Python software engineering fundamentals.
• Experience with containerised environments (Docker, Apptainer).
• Excellent understanding of machine learning theory and related math.

Responsibilities

• Design, implement and deploy ML solutions to complex biological challenges.
• Develop high-quality, maintainable software across research and operational domains.
• Collaborate with scientists, core facilities and external partners.
• Plan projects with feasibility assessments, prototyping and resource estimates.
• Lead software lifecycle from engagement to delivery and maintenance.
• Stay current in ML and share knowledge within the team.

Skills

Python

ML theory

Software engineering

HPC / Cloud

Docker

Apptainer

LangChain

LlamaIndex

Haystack

Agents

Tools

Docker

Apptainer

Job description

• 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