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- Tasks: Join a top ML engineering team tackling complex defence challenges with innovative AI/ML algorithms.
- Company: Work with the UK's leading AI Consultancy in the Defence/National Security sector.
- Benefits: Enjoy a competitive day rate, hybrid work options, and the chance to shape future technology.
- Why this job: Be part of a mission-critical project that impacts national security and drives technological advancement.
- Qualifications: Must be a British National with SC Clearance and expertise in C/C++, Python, and radar systems.
- Other info: 3-month rolling contract with immediate start; ideal for those passionate about defence technology.
The predicted salary is between 46800 - 78000 £ per year.
Day Rate: Up to £650 outside IR35
Industry: Defence/National Security
Location: Central London - Hybrid
Duration: 3 Month Rolling
Start Date: 1 Week Notice
The Opportunity: The UK’s leading AI Consultancy seeks an influential ML Engineer to push the boundaries of innovation in a mission-critical defence project.
The Role: You will join a high-performing ML engineering team of data science and AI experts solving complex challenges in Radar and Sonar Signal Processing to develop bespoke AI/ML algorithms that drive Intelligence, Surveillance, Reconnaissance, and Navigation Systems, shaping the future of defence technology.
Essential Requirements:
- British National with Central Government SC Clearance
- Proficiency in C/C++, Python, VHDL/Verilog for FPGA programming, radar simulation tools (e.g. MATLAB, Simulink), and real-time embedded systems.
- In-depth knowledge of radar principles (Doppler, pulse, continuous wave, synthetic aperture), radar signal processing, and algorithms.
- Practical experience in radar system design, development, testing, and troubleshooting, with knowledge of specific applications like military, automotive, and weather radar.
- Familiarity with machine learning (ML) domains such as NLP, Bayesian inference, deep learning, and AI safety.
- Experience with data science libraries (e.g. NumPy, Pandas, Scikit-Learn) and MLOps tools for deployment and scalability.
- Background in quantitative research (e.g. STEM PhD) or professional analyst roles, focusing on radar systems in Defence.
- Strong mathematical reasoning and understanding of statistical tests and probability.
- Research experience (PhD/Postdoc) with academic publications and conference presentations.
- Commercial experience, including customer-facing roles or project management.
For more information or to apply, please reach out to:
Contact: 02077806706
Email: george.bates@ansonmccade.com
LinkedIn: George Bates | LinkedIn
Machine Learning Engineer employer: Anson McCade
Contact Detail:
Anson McCade Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Make sure to network with professionals in the defence and AI sectors. Attend relevant conferences or meetups where you can connect with people who work in similar roles. This can help you gain insights into the industry and potentially get referrals.
✨Tip Number 2
Familiarise yourself with the latest advancements in radar signal processing and machine learning. Follow industry publications, blogs, and forums to stay updated. This knowledge will not only prepare you for interviews but also demonstrate your passion for the field.
✨Tip Number 3
Consider contributing to open-source projects related to machine learning or radar systems. This hands-on experience can enhance your skills and make your profile stand out. Plus, it shows your commitment to continuous learning and collaboration.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and algorithm problems, especially in C/C++ and Python. Use platforms like LeetCode or HackerRank to sharpen your skills. Being well-prepared will boost your confidence during the interview process.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, radar systems, and programming languages like C/C++ and Python. Emphasise any specific projects or roles that align with the job description.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for defence technology and your expertise in ML engineering. Mention how your skills can contribute to the mission-critical projects outlined in the job description.
Highlight Relevant Experience: In your application, focus on your practical experience with radar system design and development. Include any specific applications you've worked on, such as military or automotive radar, to demonstrate your suitability for the role.
Showcase Your Research Background: If you have a PhD or postdoc experience, make sure to mention your research work, publications, and presentations. This will help establish your credibility and expertise in the field of machine learning and radar systems.
How to prepare for a job interview at Anson McCade
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in C/C++, Python, and VHDL/Verilog. Bring examples of past projects where you've used these languages, especially in radar simulation or embedded systems.
✨Demonstrate Your Knowledge of Radar Principles
Familiarise yourself with key radar concepts like Doppler and synthetic aperture. Be ready to explain how these principles apply to the role and share any relevant experiences you have in radar system design.
✨Highlight Your Machine Learning Experience
Discuss your familiarity with ML domains such as NLP and deep learning. Prepare to talk about specific projects where you've implemented machine learning algorithms, particularly in defence or related fields.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving skills in real-time systems. Practice articulating your thought process clearly, as this will demonstrate your analytical abilities and approach to complex challenges.
