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

Apply Now

Sr. Machine Learning Engineer London, UK

Galytix Limited
London
1 week ago
Create job alert

Galytix (GX) is delivering on the promise of AI.

GX has built specialised knowledge AI assistants for the banking and insurance industry. Our assistants are fed by sector-specific data and knowledge and easily adaptable through ontology layers to reflect institution-specific rules.

GX AI assistants are designed for Individual Investors, Credit and Claims professionals. Our assistants are being used right now in global financial institutions. Proven, trusted, non-hallucinating, our assistants are empowering financial professionals and delivering 10x improvements by supporting them in their day-to-day tasks.

As a Sr. Machine Learning Engineer, you will need to:

  • Develop a state of the art data science and ML runtime stack in a multi-cloud environment.
  • Lead on software engineering and software design for ML components.
  • Understand and use computer science fundamentals, including data structures, algorithms, computability and complexity, and computer architecture.
  • Manage the infrastructure and pipelines needed to bring models and code into production.
  • Demonstrate end-to-end understanding of applications (including, but not limited to, the machine learning algorithms) being created.
  • Build algorithms based on statistical modelling procedures and maintain scalable machine learning solutions in production.
  • Apply machine learning algorithms and libraries.
  • Research and implement best practices to improve the existing machine learning infrastructure.
  • Collaborate with data engineers, application programmers, and data scientists.

Desired skills:

  • Qualification in a related field such as computer science, statistics, electrical engineering, mathematics, or physical sciences.
  • Self-starter with excellent communication and time management skills.
  • Strong computer programming skills, with knowledge of Python, R, and Java.
  • Experience scaling machine learning on data and compute grids.
  • Proficiency with Kubernetes, Docker, Linux, and cloud computing.
  • Experience with Dask, Airflow, and MLflow.
  • MLOps, CI, Git, and Agile processes.

Why you do not want to miss this career opportunity?

  • We are a mission-driven firm that is revolutionising the Insurance and Banking industry. We are not aiming to incrementally push the current boundaries; we redefine them.
  • Customer-centric organisation with innovation at the core of everything we do.
  • Capitalize on an unparalleled career progression opportunity.
  • Work closely with senior leaders who have individually served several CEOs in Fortune 100 companies globally.
  • Develop highly valued skills and build connections in the industry by working with top-tier Insurance and Banking clients on their mission-critical problems and deploying solutions integrated into their day-to-day workflows and processes.


#J-18808-Ljbffr

Related Jobs

View all jobs

Sr. Machine Learning Engineer

Machine Learning Engineer, AI Foundations

Machine Learning Engineer, AI Foundations

Sr. Data Scientist, GenAI Algorithms (Based in Dubai)

Data Scientist | Python | SQL | Statistics | Machine Learning | Hybrid, Oxford

Associate Director, AI Data Scientist

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 AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.

AI Team Structures Explained: Who Does What in a Modern AI Department

Artificial Intelligence (AI) and Machine Learning (ML) are no longer confined to research labs and tech giants. In the UK, organisations from healthcare and finance to retail and logistics are adopting AI to solve problems, automate processes, and create new products. With this growth comes the need for well-structured teams. But what does an AI department actually look like? Who does what? And how do all the moving parts come together to deliver business value? In this guide, we’ll explain modern AI team structures, break down the responsibilities of each role, explore how teams differ in startups versus enterprises, and highlight what UK employers are looking for. Whether you’re an applicant or an employer, this article will help you understand the anatomy of a successful AI department.

Why the UK Could Be the World’s Next AI Jobs Hub

Artificial Intelligence (AI) has rapidly moved from research labs into boardrooms, classrooms, hospitals, and homes. It is already reshaping economies and transforming industries at a scale comparable to the industrial revolution or the rise of the internet. Around the world, countries are competing fiercely to lead in AI innovation and reap its economic, social, and strategic benefits. The United Kingdom is uniquely positioned in this race. With a rich heritage in computing, world-class universities, forward-thinking government policy, and a growing ecosystem of startups and enterprises, the UK has many of the elements needed to become the world’s next AI hub. Yet competition is intense, particularly from the United States and China. Success will depend on how effectively the UK can scale its strengths, close its gaps, and seize opportunities in the years ahead. This article explores why the UK could be the world’s next global hub for artificial intelligence, what challenges it must overcome, and what this means for businesses, researchers, and job seekers.