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

Apply Now

Deep Learning Engineer

Cubiq Recruitment
Oxford
5 days ago
Create job alert

Senior & Principal Applied AI Scientists – Automated Labs & Generative Modelling


Oxford/London | Hybrid | Full-time


  • A top quartile salary designed to attract and reward world-class talent, plus comprehensive benefits (private medical, pension, income protection, enhanced holiday).
  • Electric car scheme & lifestyle perks.
  • A collaborative culture that values curiosity, resilience, and creativity.
  • You'll be working with a world-class team.


Are you ready to join one of the most ambitious and rapidly scaling AI teams being built in Europe right now?


We’re assembling an elite group of researchers and engineers, drawing talent from FAANG, leading AI scaleups, and cutting-edge academic labs, to tackle some of the biggest scientific challenges of our time.


This is your chance to apply AI and automation at scale to reimagine how discovery happens in materials science, chemistry, and the life sciences.


Why this role matters


  • Leveraging generative modelling, robotics, and autonomous experimentation to accelerate breakthroughs in chemistry, biology, and materials.
  • Partner with leading scientists, engineers, and technologists from across the globe.
  • Contribute to programmes that with strong humanitarian impact.
  • Help build automated, data-driven research pipelines that move ideas from concept to solution faster than ever before.


What you’ll do


  • Lead and contribute to the design and implementation of AI-driven discovery pipelines.
  • Apply deep learning, foundation models, and generative approaches to problems in chemistry, materials, and the biosciences.
  • Integrate with automated labs and high-throughput platforms to run closed-loop experiments.
  • Collaborate with domain experts to ensure solutions address real scientific needs.
  • Mentor and guide other scientists, setting the standard for technical excellence.


What we’re looking for


  • PhD (or equivalent) in ML/AI, computational sciences, chemistry, materials, or related fields.
  • Proven experience applying state-of-the-art ML models to real-world problems.
  • Experience with generative modelling and/or automated laboratory systems.
  • Strong track record of working with complex, large-scale scientific data.
  • Excellent communication and the ability to work across disciplines.


Nice to have


  • Experience in high-impact scientific domains (chemistry, drug discovery, materials, biology).
  • Background in start-ups or fast-paced R&D environments.

Related Jobs

View all jobs

Deep Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

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.

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.

Why the UK Could Be the World’s Next Machine Learning Jobs Hub

Machine learning (ML) is becoming essential to industries across the globe—from finance and healthcare to retail, logistics, defence, and the public sector. Its ability to uncover patterns in data, make predictions, drive automation, and increase operational efficiency has made it one of the most in-demand skill sets in the technology world. In the UK, machine learning roles—from engineers to researchers, product managers to analysts—are increasingly central to innovation. Universities are expanding ML programmes, enterprises are scaling ML deployments, and startups are offering applied ML solutions. All signs point toward a surging need for professionals skilled in modelling, algorithms, data pipelines, and AI systems. This article explores why the United Kingdom is exceptionally well positioned to become a global machine learning jobs hub. It examines the current landscape, strengths, career paths, sector-specific demand, challenges, and what must happen for this vision to become reality.