Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Software Engineer, (Data Engineering)

Isomorphic Labs
City of London
1 day ago
Create job alert

Isomorphic Labs (IsoLabs) was founded in 2021 and is led by Sir Demis Hassabis, building on the success of Google DeepMind’s AlphaFold to accelerate drug discovery with state‑of‑the‑art AI models.


Software Engineer (Data Engineering), London or Lausanne

We are here to advance human health by reimagining drug discovery with the power and pace of artificial intelligence.


Your impact

We are looking for outstanding software engineers to work on different aspects of our ML‑based software platform such as data, backend and full‑stack engineering, ML engineering, as well as technical and cloud infrastructure. We are keen on receiving applications from individuals who sit at the intersection of one or more of these fields.


What You Will Do

  • Ingestion, management and serving of scientific data
  • Backend and full‑stack engineering for the build‑out of scientific applications and data‑management tools
  • Building a state‑of‑the‑art platform for conducting ML research with high velocity and reliability
  • Building key MLOps components for transferring models from research to production at scale
  • Working on low‑level performance optimisation to increase the efficiency and performance of ML models and infrastructure
  • Optimising and maximising our compute resources and fleet of accelerators for large‑scale training and inference

Essential Skills and Qualifications

  • Strong software engineering experience with software design / architecture skills
  • Extensive enterprise programming experience writing production code using mainstream languages such as Python, Java, C++ or Go
  • Experience with Kubernetes and cloud computing
  • Experience building secure/scalable platforms/products on cloud
  • Demonstrated ability to work in multi‑disciplinary teams and environments
  • Great degree of adaptability and a willingness to work across domains and different parts of the tech stack when needed
  • Demonstrate ongoing career progression / trajectory and a passion for learning
  • MSc in computer science, or equivalent experience

Nice to have

  • Expertise in Python
  • Experience with the management of scientific and experimental wet‑lab data in a pharma context
  • Experience building backend systems for web applications, using technologies such as Django, SQLalchemy, Pydantic, PostgreSQL
  • Experience designing, implementing and maintaining relational data models with Python‑based interfaces
  • Experience developing frontend applications in a scientific context
  • Experience building, optimising and productionising large‑scale deep‑learning models
  • Hands‑on experience with cloud engineering in a compute‑heavy environment, preferably on GCP
  • Hands‑on experience optimising the use of fleets of hardware accelerators
  • Experience with low‑level hardware specific optimisation for deep learning
  • Experience with life‑sciences data, including bioinformatics, computational chemistry, and biomedical research data

Culture and Values

We are guided by our shared values. These values help to guide our work and will continue to strengthen it.


Thoughtful

Thoughtful at Iso is about curiosity, creativity and care. It is about good people doing good, rigorous and future‑making science every single day.


Brave

Brave at Iso is about fearlessness, but it’s also about initiative and integrity. The scale of the challenge demands nothing less.


Determined

Determined at Iso is the way we pursue our goal. It’s a confidence in our hypothesis, as well as the urgency and agility needed to deliver on it.


Together

Together at Iso is about connection, collaboration across fields and catalytic relationships. It’s knowing that transformation is a group project, and remembering that what we’re doing will have a real impact on real people everywhere.


Hybrid working

It’s hugely important for us to share knowledge and build strong relationships with each other, and we find it easier to do this if we spend time together in person. This is why we follow a hybrid model, and would require you to be able to come into the office 3 days a week (currently Tuesday, Wednesday and one other day depending on the team).


We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding) or any other basis protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.


#J-18808-Ljbffr

Related Jobs

View all jobs

Software Engineer / Machine Learning Developer

Software Engineer - Machine Learning

Software Engineer - (Machine Learning Engineer) - Hybrid

Software Engineer - (Machine Learning Engineer) - Hybrid

Software Engineer (Leadership) - Machine Learning

Software Engineer - (Machine Learning Experience a plus) - hybrid

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.