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- Tasks: Design and deploy cutting-edge machine learning systems for MI6's operational needs.
- Company: Join MI6, the UK's Secret Intelligence Service, at the forefront of AI innovation.
- Benefits: Competitive salary, unique work environment, and opportunities for professional growth.
- Other info: Dynamic role with a focus on ethical AI and significant career development.
- Why this job: Make a real impact in national security using advanced machine learning technologies.
- Qualifications: Experience in ML lifecycle, deployment, and collaboration within technical teams.
The predicted salary is between 40000 - 50000 £ per year.
Location: London
At MI6 (the Secret Intelligence Service), we're investing heavily in artificial intelligence and machine learning to strengthen how we operate today and prepare for the challenges of tomorrow. As a Machine Learning Engineer, you'll be a key part of that transformation.
You'll be working at the point where machine learning moves into live, operational use, designing, deploying and maintaining robust capabilities in environments where quality, resilience and trust are paramount.
What you'll be working on:
- Design, build and operate mission critical machine learning systems
- Own the end to end ML lifecycle, from training and fine tuning through to deployment and live monitoring
- Act as the bridge between research and production, ensuring models are reliable, scalable and fit for purpose
- Shape and improve MLOps practices, infrastructure and workflows
- Champion explainable, ethical and transparent AI as core engineering principles
- Collaborate with data scientists, researchers, software engineers and hosting specialists
- Support and mentor other engineers, helping to raise ML capability across teams
Who we're looking for:
You might be:
- A Machine Learning Engineer with end to end deployment experience
- A Software Engineer who has built and run applied ML systems
- A Data Scientist with strong engineering and mathematical foundations
What matters most is that you:
- Understand the full ML lifecycle
- Have experience deploying, monitoring and optimising models in live environments
- Are comfortable working with MLOps tooling, cloud platforms and Python
- Can work calmly with ambiguity and think beyond the immediate task
- Communicate clearly and collaborate well within technical communities
Experience with tools such as Weights & Biases, Docker or Kubernetes is helpful, but not essential.
Important to know:
Due to the nature of the work, the role is based in London, and the recruitment process includes enhanced security checks.
Find out more & apply via Civil Service Jobs.
Machine Learning Engineer - MI6 - HEO employer: Government Digital & Data
Contact Detail:
Government Digital & Data Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer - MI6 - HEO
✨Tip Number 1
Network like a pro! Reach out to current or former employees at MI6 on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by brushing up on your ML knowledge. Be ready to discuss your experience with the full ML lifecycle and how you've tackled challenges in live environments. We want to see your problem-solving skills in action!
✨Tip Number 3
Showcase your projects! If you've built or deployed any machine learning systems, make sure to highlight them during your discussions. We love seeing practical examples of your work and how you’ve made an impact.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the team at MI6 and contributing to our mission.
We think you need these skills to ace Machine Learning Engineer - MI6 - HEO
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Machine Learning Engineer role. Highlight your end-to-end ML lifecycle experience and any relevant projects you've worked on. We want to see how you can contribute to our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and machine learning, and how your background makes you a great fit for MI6. Don’t forget to mention your collaborative spirit and how you can help us champion ethical AI.
Showcase Your Technical Skills: Be sure to include any specific tools or technologies you've worked with, like Python, Docker, or MLOps tooling. We love seeing practical examples of how you've deployed and monitored models in live environments, so don’t hold back!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details you need about the role and the recruitment process there!
How to prepare for a job interview at Government Digital & Data
✨Know Your ML Lifecycle
Make sure you can confidently discuss the entire machine learning lifecycle. Be prepared to explain how you've handled each stage, from training and fine-tuning models to deployment and live monitoring. This shows that you understand the complexities involved in bringing ML systems to life.
✨Showcase Your Collaboration Skills
Since you'll be working with a variety of professionals, it's crucial to demonstrate your ability to collaborate effectively. Share examples of past projects where you worked alongside data scientists, software engineers, or researchers. Highlight how you communicated complex ideas clearly and contributed to team success.
✨Emphasise Ethical AI Practices
MI6 values explainable and ethical AI, so be ready to discuss how you've incorporated these principles into your work. Talk about any experiences you have with ensuring transparency in your models and how you’ve addressed potential biases. This will show that you align with their core engineering principles.
✨Prepare for Technical Questions
Expect technical questions related to MLOps tooling, cloud platforms, and Python. Brush up on your knowledge of tools like Docker and Kubernetes, even if they're not essential. Practising coding problems or discussing your past projects can help you feel more confident when answering these questions.