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- Tasks: Design and deploy AI systems for defence and security using cutting-edge machine learning.
- Company: Leading technology company focused on high-stakes environments.
- Benefits: Competitive salary, security clearance support, and collaborative team environment.
- Why this job: Make a real impact in national security while working with advanced AI technologies.
- Qualifications: Strong Python skills and operational experience with ML models required.
- Other info: On-site work up to three days a week across various London locations.
The predicted salary is between 43200 - 72000 £ per year.
A leading technology company is seeking a Machine Learning Engineer to design and deploy AI systems in high-stakes defence and security environments. This role involves building production-grade ML solutions and collaborating with various teams to ensure effective deployment.
The ideal candidate should have:
- Strong Python skills
- Operational experience with ML models
- Eligibility for UK Security Clearance
- Willingness to work on-site up to three days a week across locations including London
Production ML Engineer – Defence & National Security in London employer: Anson McCade
Contact Detail:
Anson McCade Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Production ML Engineer – Defence & National Security in London
✨Tip Number 1
Network like a pro! Reach out to folks in the defence and security sectors on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your ML projects, especially those relevant to defence. This will give you an edge when discussing your experience.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on Python and ML concepts. Mock interviews with friends can help you feel more confident.
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining us. Tailor your application to highlight your passion for ML in defence.
We think you need these skills to ace Production ML Engineer – Defence & National Security in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your Python skills and any relevant experience with ML models. We want to see how your background aligns with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about defence and national security, and how your skills can contribute to our mission. Keep it concise but impactful!
Showcase Your Projects: If you've worked on any production-grade ML solutions, make sure to mention them! We love seeing real-world applications of your skills, so include links or descriptions of your projects that demonstrate your expertise.
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’s super easy!
How to prepare for a job interview at Anson McCade
✨Know Your ML Models Inside Out
Make sure you can discuss the machine learning models you've worked with in detail. Be prepared to explain how you built them, the challenges you faced, and how you overcame those challenges. This will show your operational experience and technical depth.
✨Brush Up on Python Skills
Since strong Python skills are a must for this role, take some time to review key libraries and frameworks relevant to machine learning. Be ready to demonstrate your coding abilities, perhaps even through a live coding exercise during the interview.
✨Understand Defence & Security Context
Familiarise yourself with the specific challenges and requirements of deploying AI systems in defence and national security environments. Showing that you understand the stakes involved will set you apart from other candidates.
✨Prepare for Team Collaboration Questions
This role involves working with various teams, so be ready to discuss your experience in collaborative projects. Think of examples where you successfully worked with others to deploy ML solutions, highlighting your communication and teamwork skills.
