Machine Learning Engineer / Data Scientist

Job description

We need ML specialists with a strong pragmatic and execution focus to help us build products that generate actionable intelligence for human analysts.  In particular, we need people with specific expertise in Graph Theory and Time Series Analysis, or other comparable computational statistics skills.

Along with evidence of an academic background in Machine Learning or Data Science, we are looking for people with an ability to use theoretical models in the real world on real data.

We all know that the amount of unstructured data - emails, documents, social media, web content, images and video - is exploding.  We also know that generating actionable intelligence from this data is time consuming and inefficient.

We think people should spend time doing the stuff that people do well, and let the machines do the stuff that machines do better.  We apply our expertise to tackle our customers’ challenges, freeing people to do what they do faster and better.  We build our AI and ML technology into products that are easy to deploy, manage and use.  We want all our tools to augment and empower knowledge-intensive processes and to help our customers efficiently and effectively analyse large volumes of data.  

Our customers are engaged in some of the most important and challenging work in the UK and around the globe, analysing billions of data points each day. The volume and complexity of their data is growing rapidly and represents a significant opportunity for us to make a positive and significant impact for our customers.

We have a small and growing team with decades of experience applying ML and AI in the real world. Our team specialise in Natural Language Processing, Complex Network and Graph Theory, Time Series Analysis, CI/CD Cloud Solutions, Distributed System Architectures and Microservices.  We have senior bankers and junior developers, PhDs and self-taught hackers. Whatever your background, we hope you would like to find a home in our inclusive and diverse team.

We pride ourselves on our close academic relationships with many of the UK’s leading software engineering and ML universities where we aim to apply cutting-edge research as soon as it is viable to real world, client-led problems.  We hold quarterly hackathons, where we take a break from the sprint rhythm, take some of those blue-sky ideas, and encourage ourselves to make something happen! 

Adarga is one of the few companies in the UK making Artificial Intelligence work on the ground, today, in real products. If you have a passion for making products that analyse vast amounts of data faster, more accurately and more effectively, then why not help us build a better data future?


  • Academic qualifications in numerate discipline with evidence of Machine Learning / Data Science components or specialisation

  • Strong software development skills, (e.g. Python)

  • Experience with either standard (SQL based) or graph-based databases

Nice to have but not mandatory:

  • Experience with Typescript, Java, R, Matlab or Octave

  • Experience with PostgreSQL, ElasticSearch or Neo4j

  • Practical experience with Agile development and Peer Code Review

  • Confident in presenting technical work to both technical and non-technical audiences