At a Glance
- Tasks: Design and develop innovative AI solutions for Defence and National Security.
- Company: Join Adarga, the UK's only sovereign Defence Tech company focused on applied AI.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Make a real impact by solving complex challenges with cutting-edge AI technology.
- Qualifications: Advanced degree in Computer Science or related field; 3+ years of ML experience.
- Other info: Dynamic team environment with a mission-driven culture and excellent career prospects.
The predicted salary is between 36000 - 60000 £ per year.
About Adarga
Adarga is the UK's only sovereign Defence Tech company specialising in applied AI solutions across intelligence, operations and planning. In an era of information overload, Adarga delivers technology that enables our mission partners to act with speed, clarity and confidence. By unlocking the value of their data, we help our partners make better decisions that achieve mission-critical outcomes.
Our team is a hybrid of domain specialists and technologists. We believe this layering of experience is key to building cutting edge AI that is operationally relevant, solving real problems, to drive real outcomes. This is a unique time to join Adarga. With our foundations set in NLP, computational linguistics and graph technology we now draw on the latest ideas in generative AI and knowledge representation, as we set our sights firmly on defining and building the next era of sovereign AI capability for mission partners across the Defence and National Security sectors.
To work at Adarga you have to care deeply about the mission. We exist to support those with the ultimate task: upholding the liberties and values that define our society. In today's contested, multipolar world, this cannot be taken for granted. We want people who are comfortable with uncertainty, who want to own decisions, who want to drive a vision. If that is you, get in touch! If you don't match all the skills and qualifications but care about our mission then we'd encourage you to back yourself and apply anyway. We all learn by doing.
About the role:
You will be joining our Product org, a cross functional team of software engineers, machine learning specialists, domain experts and product specialists, focussed on building a suite of capabilities for intelligence analysts working across Defence and National Security. You will build AI products designed to move the human up the value chain thereby enabling intelligence analysts to act with speed, clarity and confidence.
We are looking for someone to leverage their expertise in AI/ML engineering to design, develop, and deploy innovative machine learning and algorithmic solutions. We want someone adept at building models that solve hard problems.
Responsibilities
- Design and develop machine learning models and algorithmic solutions that address complex, real-world challenges for users in Defence and National Security.
- Partner with product managers, product engineers, and domain experts to deliver ML-powered features from concept through to production.
- Engineer solutions with a deep understanding of algorithmic complexity and the operational cost of running models at scale.
- Communicate model choices, assumptions, and tradeoffs with clarity - whether you're speaking to fellow engineers, product stakeholders, or end users.
- Contribute to the development of robust, user-facing AI capabilities that are both high-performing and reliable - shipped fast, and iterated with care.
- Take full ownership of your work: from early experimentation through to deployment, monitoring, and ongoing optimisation.
- Help maintain the health and resilience of our production systems, debugging distributed pipelines when things go wrong.
- Stay close to the frontier of ML and AI research, continuously exploring ways to apply emerging techniques and tools to deliver better outcomes for users.
Skills and Qualifications
- Advanced degree (Master's or PhD) in Computer Science, Machine Learning, NLP, or a related technical field.
- 3+ years of hands-on experience applying machine learning in production settings, ideally within enterprise or mission-critical environments.
- Practical expertise with Generative AI techniques—fine-tuning and evaluating large language models (LLMs), building RAG pipelines, and experimenting with agentic AI workflows.
- Strong Python development skills and familiarity with modern ML and NLP frameworks and tooling (e.g. Hugging Face, spaCy, PyTorch, Scikit-learn).
- Familiarity with Kubernetes and infrastructure for deploying and scaling ML models is a plus.
- Exposure to systems integration challenges (e.g. connecting ML workflows with data stores like PostgreSQL or search systems like Elasticsearch) is valued.
- Clear, confident communicator who thrives in cross-functional settings and can bridge the gap between technical depth and product impact.
- A curious mindset - you stay sharp by experimenting with new tools and refining your approach based on what works.
Interview Process
- Phone Interview – Remote (30 mins)
- Technical Interview – Remote/In person (1 h)
- Final Interview – Onsite (1 h)
Successful applicants may be required to undergo national security vetting upon appointment or during employment in this role. Applicants must meet the security requirements set out by UK Security Vetting (UKSV), and understand what is required in the associated UKSV: Vetting Guidance before they can be appointed.
AI Engineer in London employer: Adarga Ltd
Contact Detail:
Adarga Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Adarga. LinkedIn is your best mate here—send connection requests and drop them a message about your interest in AI engineering. You never know who might help you get your foot in the door!
✨Tip Number 2
Prepare for those interviews! Brush up on your technical skills and be ready to discuss your past projects. Make sure you can explain your model choices and how they solve real-world problems. Practice makes perfect, so do some mock interviews with friends or use online platforms.
✨Tip Number 3
Show your passion for the mission! Adarga is all about supporting defence and national security. In your conversations, highlight why you care about this field and how your skills can contribute to their goals. Authenticity goes a long way!
✨Tip Number 4
Don’t hesitate to apply through our website! Even if you don’t tick every box, if you’re excited about the role and the mission, go for it. We believe in learning by doing, so back yourself and submit that application!
We think you need these skills to ace AI Engineer in London
Some tips for your application 🫡
Show Your Passion for the Mission: When writing your application, let your enthusiasm for our mission shine through. We want to see that you care about upholding the values of society and are excited about using AI to make a difference in Defence and National Security.
Tailor Your Experience: Make sure to highlight your relevant experience in AI/ML engineering. We’re looking for specific examples of how you've tackled complex problems and delivered innovative solutions, so don’t hold back on the details!
Communicate Clearly: Your ability to communicate technical concepts is key. Use clear language to explain your model choices and assumptions, as if you were talking to someone who might not have a technical background. This will show us you can bridge the gap between tech and impact.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re proactive and keen to join our team!
How to prepare for a job interview at Adarga Ltd
✨Know Your AI Stuff
Make sure you brush up on your machine learning and AI knowledge, especially around generative AI techniques. Be ready to discuss your hands-on experience with models and algorithms, as well as any challenges you've faced in production settings.
✨Communicate Clearly
Since you'll be working with cross-functional teams, practice explaining complex technical concepts in simple terms. Think about how you can convey your model choices and trade-offs clearly to both technical and non-technical stakeholders.
✨Show Your Curiosity
Adarga values a curious mindset, so come prepared to discuss the latest trends in AI and ML. Share examples of how you've experimented with new tools or techniques and how that has improved your work or outcomes.
✨Emphasise Ownership
Be ready to talk about projects where you've taken full ownership, from design to deployment. Highlight your experience in monitoring and optimising models, and how you've tackled issues in production systems.