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- Tasks: Design and deploy impactful AI systems for defence and national security.
- Company: Leading AI consultancy with a focus on human-centric solutions.
- Benefits: Competitive salary, hybrid working, and opportunities for career growth.
- Why this job: Make a real difference in high-stakes projects while working with cutting-edge technology.
- Qualifications: Strong software engineering skills and experience in machine learning lifecycle.
- Other info: Join a dynamic team and shape the future of applied AI.
The predicted salary is between 48000 - 72000 £ per year.
ML Engineer –
Must hold active DV Clearance
This is an exciting time to join a team to help pioneer both customer\’s and an AI adoption journey.
Not only will you be directly making a huge impact through the solutions you develop, youll be doing it for an organisation who makes a huge impact to the security of the UK.
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
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's GitHub repos or a personal website, let your work speak for itself and demonstrate your expertise in Python and ML frameworks.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to engage with both technical and non-technical stakeholders.
✨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, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Machine Learning Engineer role. Highlight your software engineering skills, cloud experience, and any relevant projects you've worked on. We want to see how you can contribute to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI in defence and national security. Share specific examples of your work with machine learning and how it aligns with our mission at StudySmarter.
Showcase Your Technical Skills: Don’t just list your technical skills; demonstrate them! If you’ve deployed models using PyTorch or TensorFlow, mention those experiences. We love seeing practical applications of your knowledge, so be specific about your contributions.
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 Anson McCade
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and ML frameworks like PyTorch and TensorFlow. Brush up on your cloud experience with AWS, Azure, or GCP, as well as Docker and Kubernetes. Being able to discuss your hands-on experience confidently will impress the interviewers.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific projects where you've designed, built, or deployed machine learning systems. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will help you clearly demonstrate your ability to tackle complex challenges and deliver impactful solutions.
✨Communicate Effectively
Since you'll be working with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. Think about how you can convey your ideas clearly and concisely, ensuring everyone understands your contributions and the value of your work.
✨Emphasise Team Collaboration
Highlight your experience working in cross-functional teams. Be ready to share examples of how you've collaborated with engineers, data scientists, and product managers. This shows that you can thrive in a team environment and contribute to the overall success of projects.
