Research Engineer

Location: Oxford or London (Hybrid)

The Mission: Why We Exist

Genomics is a science-led transatlantic TechBio combining large-scale genetic and health data with proprietary analytics to accelerate drug discovery and advance predictive, preventative healthcare. We are united by a single vision to help people live longer healthier lives, using the power of genomics.

Genomics aims to help people live longer, healthier lives in two ways: super-charging drug discovery and development for novel treatments with our AI-enabled advanced genetic analytics platform, and by helping people understand their personal risk of common chronic diseases through polygenic risk scores - giving doctors and health systems the chance to get the right people into the right prevention, screening and treatment programmes at the right time.

Role Purpose

We're looking for an exceptional Research Engineer with strong computational skills and a track record of applying them to large-scale data science. A background in human genetics is preferred, but if you come from another quantitative field and are excited by the potential of genetics to transform healthcare, we'd love to hear from you.

You'll join a team of experts in human genetics, data science and software engineering, building the platform at the heart of our Life Sciences work – (1) helping us derive new insights into human biology and guide drug development towards safer, more effective targets; (2) providing our SaaS customers with innovative analytics. How your time splits across methodology, software engineering and analysis will reflect your own balance of computational and scientific strengths.

This role can be hired at IC2 (Research Engineer) or IC3 (Senior Research Engineer) level, depending on your experience. At IC3, you'll operate with greater autonomy, hold a broader technical scope, bring deeper subject-matter expertise, and lead projects that require integrated updates across multiple tools, working with cross-disciplinary teams to deliver value.

A Day in the Life

At the heart of this role is the opportunity to collaborate with domain experts at the cutting edge of statistical genetics and rapidly translate their innovations into a mature, integrated data & analytics engine for commercial use at scale.

• Help expand and maintain our in-house Life Sciences tools and pipelines, planning your own work and contributing code to a shared codebase alongside Research Engineering team members, Software Engineers and Data Scientists.
• Implement algorithms developed within our Life Sciences teams to a high standard of robustness, testing and performance.
• Run high-quality analyses of large-scale biological datasets using existing or bespoke tools, and share your findings with scientists and other stakeholders.
• Contribute to internal and external presentations and publications arising from our work.
• Keep your knowledge current on innovation and good practice in genomics, data science and scientific computing.
• At Senior (IC3) level, you'll also lead projects that need integrated updates across multiple tools, coordinating with cross-disciplinary teams to deliver value.

Who You Are

Essential

• A strong quantitative background in a scientific field, with the ability to explain complex ideas to specialists and non-specialists alike.
• Skilled at writing high-quality Python code using modern software development practices.
• Confident analysing and learning from large-scale datasets in a scientific context.
• Experienced running tools and workflows in a scalable system, for example Linux based HPC environments or on cloud systems.
• Comfortable using LLM programming assistants appropriately within a research software environment.

It'd be great if you also have

• Experience working on a collaborative codebase using version control and CI/CD.
• Familiarity with common bioinformatics and genomics tools and file formats.
• Experience designing and running large-scale workflows, e.g. WDL, CWL.
• Experience working in remote, cloud-based environments, e.g. AWS.
• Experience creating and working with containers, e.g. Docker, Singularity.
• Additional programming languages, particularly R or C++.
• A PhD or postgraduate degree in a scientific field, ideally genomics, bioinformatics or computational biology, with familiarity in statistics and machine learning.
• Prior experience working in a team, ideally in an industry setting.

Your Package

We are committed to providing a transparent, supportive, and rewarding work environment.

Compensation & Growth

• Competitive Salary : Salaries are externally benchmarked annually to ensure competitive compensation.
• Clear Career Path: A straightforward, open progression framework means you'll always know the path to promotion and how to achieve your next career goal.
• Continuous Learning: Including external courses and a wide library of L&D materials, because your growth is our success.

Wellbeing & Time Off

• Holiday: 25 days annual leave, plus bank holidays, plus an extra 3-day company-wide shutdown at year-end.
• Financial & Health Security: Robust benefits including a market-leading pension scheme, comprehensive private health insurance for you and your family with NO excess, critical illness, and life assurance.
• Enhanced Leave : Enhanced paid family leave to support all new parents.

Work Environment & Culture

• Flexible Working: Hybrid Working (e.g., From our London, Oxford Office)
• Truly Inclusive Time Off: Our 'Bank Your Bank Holiday' program allows you to exchange public holidays for dates that hold personal or cultural significance to you.
• Vibrant Social Culture: From regular Town Halls and team picnics to organised sports events, our social committee ensures frequent opportunities to connect and celebrate.
• Green Commute: Cycle-to-Work scheme and convenient office locations near major transport hubs.

We are dedicated to creating a diverse environment and are proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

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