At a Glance
- Tasks: Design and implement cutting-edge machine learning systems in a dynamic defence tech environment.
- Company: Join a growing defence-tech consultancy with top-tier engineers.
- Benefits: Competitive salary, bonus, private healthcare, pension, and generous holiday allowance.
- Other info: Work in small teams on innovative projects with excellent career growth opportunities.
- Why this job: Tackle unique challenges and make a real impact in AI solutions.
- Qualifications: Strong understanding of machine learning, statistics, and LLM principles.
The predicted salary is between 50000 - 100000 € per year.
A growing defence-tech consultancy is seeking Machine Learning Engineers of various levels and disciplines to work on advanced AI solutions and/or design and implement machine learning systems, including LLM applications within secure environments. You'll genuinely be working alongside some of the best engineers/teams in the country, solving problems no one else has before. They are deliberately setting a very high bar, hiring engineers from top universities who are among the strongest technically in their field.
The work is very problem-solving focused, small teams tackling complex systems, often working on completely new challenges every few months. They’re hiring for, and value, people who:
- Enjoy working on challenging systems
- Are friendly
- Truly understand problem-solving principles
- Enjoy variety
- Are adaptable and articulate
Machine Learning Engineer Responsibilities may include:
- Applying machine learning fundamentals and statistical techniques
- Working with LLMs and transformer architectures
- Evaluating model performance and optimising inference
- Developing solutions for constrained or secure environments
- Supporting explainability, safety, and robustness of AI systems
- Integrating AI/ML components into applications and workflows
- Designing and implementing retrieval-augmented generation systems
- Evaluating LLM performance and mitigating failure modes
- Testing and debugging non-deterministic systems
- Assessing when AI vs deterministic approaches are appropriate
Machine Learning Engineer Requirements:
- Deep understanding of machine learning fundamentals
- Strong mathematics and statistics knowledge
- LLM principles and transformer architectures
- LLM performance evaluation and inference optimisations
- Developing modules for edge, constrained or air-gapped environments would be a plus
- Explainable AI or AI safety/security would be a plus
- Applied AI overlap: Integrating AI components into applications and workflows
- LLM evaluation, failure modes, and mitigation strategies
- Testing and debugging non-deterministic systems
- Retrieval-Augmented Generation
- Understanding of the risks and limitations of AI and where statistical models or deterministic logic would be more appropriate
- Understanding of core AI/ML concepts such as LLM architectures, ML models, and statistical methods
Additional Criteria:
- STEM Degree from a leading university (2:1 or 1st class)
- Eligibility for UK SC-level security clearance
- Experience in defence or highly regulated environments is advantageous, but not required
Machine Learning Engineer Benefits:
- Target based Bonus (~10%)
- Private healthcare
- Pension
- 25 days holiday + bank holidays
Machine Learning Engineer | Defence Start-up employer: Switch Tech Talent
Join a pioneering defence-tech start-up in Newcastle, where you'll collaborate with some of the brightest minds in engineering to tackle unique challenges in machine learning and AI. With a strong emphasis on employee growth, a supportive work culture, and competitive benefits including a target-based bonus and private healthcare, this is an exceptional opportunity for those looking to make a meaningful impact in a dynamic environment.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer | Defence Start-up
✨Tip Number 1
Network like a pro! Reach out to people in the defence tech space, especially those already working at the company you're eyeing. A friendly chat can give you insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your machine learning projects. This is your chance to demonstrate your problem-solving abilities and technical prowess in a way that a CV just can't.
✨Tip Number 3
Ace the interview by practising common ML scenarios and problem-solving questions. We recommend doing mock interviews with friends or using online platforms to get comfortable with articulating your thought process.
✨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 genuinely interested in joining our team!
We think you need these skills to ace Machine Learning Engineer | Defence Start-up
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with LLMs, transformer architectures, and any relevant projects that showcase your problem-solving skills. We want to see how you fit into our defence-tech world!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about working in defence tech and how your skills align with our needs. Be sure to mention specific experiences that demonstrate your adaptability and problem-solving abilities.
Showcase Your Projects:If you've worked on any machine learning projects, especially those involving AI safety or explainability, make sure to include them in your application. We love seeing real-world applications of your skills, so don’t hold back!
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 keen on joining our team at StudySmarter!
How to prepare for a job interview at Switch Tech Talent
✨Know Your Stuff
Make sure you brush up on your machine learning fundamentals and the latest in LLMs and transformer architectures. Be ready to discuss specific projects you've worked on, especially those that involved problem-solving in complex systems.
✨Show Your Problem-Solving Skills
Prepare to tackle hypothetical scenarios during the interview. Think about how you would approach a new challenge or optimise a model's performance. This is your chance to showcase your analytical thinking and adaptability.
✨Be Friendly and Articulate
Since the company values a friendly atmosphere, don’t forget to let your personality shine through. Practice explaining complex concepts in simple terms, as communication is key when working in small teams.
✨Understand the Defence Context
Familiarise yourself with the unique challenges of working in defence tech. Even if you don't have direct experience, showing an understanding of the importance of security and explainability in AI systems will set you apart.
