At a Glance
- Tasks: Design and build mission-critical machine learning capabilities to enhance national security.
- Company: Join MI6, the UK's Secret Intelligence Service, dedicated to protecting national security.
- Benefits: Competitive salary, generous leave, pension scheme, and professional development opportunities.
- Other info: Diverse and inclusive workplace with excellent career growth and training support.
- Why this job: Make a real impact on national security while working with cutting-edge AI technologies.
- Qualifications: Experience in machine learning lifecycle, model deployment, and cloud environments.
The predicted salary is between 63823 - 63823 £ per year.
Flexible working: we support full time, part time (minimum three days a week), compressed hours, job share and other flexible working patterns. Due to the sensitive nature of our work, this role is primarily office based. Home working is not guaranteed and is based on business needs.
About us
We're MI6, also known as the Secret Intelligence Service (SIS). Our mission is to protect the security and economic wellbeing of the UK from overseas threats such as regional instability, terrorism, and cyber‐attacks. Working across the globe and in close partnership with MI5 and GCHQ, we help the Government to counter these threats through the provision of secret intelligence. A role in MI6 will see you providing vital support to this work, within a supportive and encouraging environment that puts the emphasis on teamwork.
The role
Enhancing how we operate today will better prepare us for the challenges of tomorrow. That's why we're creating dedicated teams focused on bringing Artificial Intelligence (AI) into some of our most mission critical areas. As a Machine Learning Engineer, you'll be at the heart of our efforts, working with our technical teams to design, build and operate mission‐critical machine learning capabilities. This includes everything from infrastructure and MLOps through to training, fine‐tuning, deployment, and live model management. While you'll be hands‐on in engineering, your work will also be advisory, ensuring models are reliable, scalable and fit for use.
Day to day, you'll collaborate with multidisciplinary teams of data scientists, researchers, and hosting specialists, acting as the subject‐matter expert for ML deployment, reliability, and best practice. You'll be the critical bridge between research and production, making sure ideas don't stay theoretical but instead become robust, impactful systems.
A large part of your role will be leading on the technical evaluation of environments and workflows, driving innovation‐led initiatives, and continuously improving how we monitor, measure, and optimise model performance. Just as importantly, you'll champion model explainability, transparency, and ethical AI as core engineering principles. Across multiple projects, you'll also support and mentor junior ML engineers, help software engineers design ML‐ready hosting environments, and translate complex systems into a clear, practical understanding for non‐technical stakeholders.
About you
There's no single route into this role – what matters most is your genuine, end‐to‐end understanding of the ML lifecycle and real, practical experience of model deployment, monitoring, and optimisation. This may come from working as a Machine Learning Engineer already, years spent as a Software Engineer building applied ML systems, or a data science background grounded in strong mathematical foundations.
You'll have seen at least one full project lifecycle through from start to finish, ideally within an environment with centralised standards and platforms. With your background of managing model lifecycles and deployments, you'll know what it takes to fine‐tune and operationalise models in live environments, and you'll be comfortable working across platforms with the ability to adapt to customer‐embedded models as needs evolve. Hands‐on experience working alongside scientists and within deployment environments is central to this role, as is familiarity with MLOps tooling, scheduling, and orchestration. You'll be comfortable working in cloud environments and with ML lifecycle tools such as Weights & Biases, and you'll have Python experience too. Experience with Docker or Kubernetes is beneficial, but not essential.
You're also curious, self‐directed, and always keen to learn more. You're comfortable with ambiguity, calm under pressure, and able to see beyond the immediate task. You communicate clearly, work well within technical communities, and bring the resilience to keep things moving should any obstacles arise.
Training and development
We take professional development seriously, and you'll be joining a community that invests in helping people grow their skills. You'll have access to a broad mix of learning opportunities, including in‐house and online training, technical deep dives and development pathways shaped around your interests and the needs of the organisation. This includes support to strengthen your capability across modern AI techniques, Cloud technologies and wider analytical or engineering practices.
We use the Government Digital and Data Profession Capability Framework (formerly known as DDaT) as a compass to provide guidance and tools to support you. You can find out more about the framework on the Government Digital and Data Profession Capability Framework page. You'll also have opportunities to work with external professional bodies and training providers who offer routes to specialist accreditation, advanced AI training or broader professional recognition. Whether you choose to deepen your expertise in a specific technical area or broaden your capability across new domains, you'll have the guidance and support you need to progress.
Rewards and benefits
You'll receive a starting salary of £63,823 plus other benefits including:
- 25 days of annual leave automatically rising to 30 days after 5 years' service, and an additional 10.5 days of public and privilege holidays
- Opportunities to be recognised through our employee performance scheme
- An interest‐free season ticket loan
- An excellent pension scheme
- A cycle‐to‐work scheme
- Facilities such as a gym, restaurant and on‐site coffee bars (at some locations)
- Paid parental and adoption leave
- Interest‐free loan to assist with relocation into privately rented accommodation (subject to availability)
Equal opportunities
At MI6 diversity and inclusion are critical to our mission. To protect the UK, we need a truly diverse workforce that reflects the society we serve. This includes diversity in every sense of the word: those with different backgrounds, ages, ethnicities, gender identities, sexual orientations, ways of thinking and those with disabilities or neurodivergent conditions. We therefore welcome and encourage applications from everyone, including those from groups that are under‐represented in our workforce such as women, those from an ethnic minority background, people with disabilities, and those from low socio‐economic backgrounds.
Eligibility & requirements
To work at MI6, you need to be a British citizen or hold dual British nationality. This role requires the highest security clearance, known as Developed Vetting (DV). Please review the vetting process and eligibility criteria before applying.
Machine Learning Engineer Ref. 3722 in London employer: UK Intelligence Services
At MI6, we pride ourselves on being an exceptional employer, offering a supportive and collaborative work environment that prioritises teamwork and professional growth. As a Machine Learning Engineer, you'll benefit from flexible working arrangements, extensive training opportunities, and a commitment to diversity and inclusion, all while contributing to the vital mission of safeguarding the UK. With access to modern facilities and a comprehensive benefits package, including generous leave and pension schemes, MI6 is dedicated to fostering a rewarding career for its employees.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer Ref. 3722 in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees on LinkedIn, and ask them about their experiences. A friendly chat can give you insider info and might even lead to a referral.
✨Tip Number 2
Prepare for the interview by brushing up on your technical skills. Make sure you can talk confidently about your experience with machine learning, MLOps, and any relevant projects you've worked on. Practice common interview questions too!
✨Tip Number 3
Show your passion for AI and machine learning! During interviews, share your thoughts on the latest trends in the field and how they could impact MI6's mission. This will demonstrate your enthusiasm and commitment to the role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining our team at MI6.
We think you need these skills to ace Machine Learning Engineer Ref. 3722 in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Machine Learning Engineer role. Highlight your relevant experience with ML lifecycle, deployment, and any specific tools mentioned in the job description. We want to see how your skills align with our mission!
Showcase Your Projects:Include details about projects you've worked on that demonstrate your hands-on experience with machine learning. Whether it's a full project lifecycle or specific challenges you've tackled, we love seeing real-world applications of your skills.
Be Clear and Concise:When writing your application, keep it straightforward and to the point. Use clear language to explain your experience and avoid jargon unless necessary. We appreciate clarity as much as technical expertise!
Apply Through Our Website:Don’t forget to submit your application through our official website. It’s the best way to ensure your application gets into the right hands. Plus, it shows you’re serious about joining our team at MI6!
How to prepare for a job interview at UK Intelligence Services
✨Know Your ML Lifecycle
Make sure you can clearly articulate your understanding of the machine learning lifecycle. Be prepared to discuss specific projects you've worked on, focusing on model deployment, monitoring, and optimisation. This will show that you have the practical experience needed for the role.
✨Showcase Your Technical Skills
Brush up on your Python skills and be ready to discuss any MLOps tools you've used, like Weights & Biases. If you have experience with Docker or Kubernetes, mention it! Highlighting your technical expertise will demonstrate your readiness for the hands-on aspects of the job.
✨Emphasise Team Collaboration
Since the role involves working with multidisciplinary teams, be prepared to share examples of how you've collaborated with data scientists, researchers, or software engineers in the past. This will illustrate your ability to bridge the gap between research and production effectively.
✨Discuss Ethical AI Practices
Given the importance of ethical AI in this role, come equipped with thoughts on model explainability and transparency. Be ready to discuss how you've championed these principles in your previous work, as this aligns closely with the values of MI6.
