At a Glance
- Tasks: Design and deploy machine learning systems for impactful national security projects.
- Company: Leading applied AI consultancy with a focus on innovation.
- Benefits: Competitive salary, hybrid work model, and opportunities for mentorship.
- Other info: Fast-paced environment with excellent career growth and learning opportunities.
- Why this job: Join a team of experts and make a difference in real-world applications.
- Qualifications: Strong Python skills and experience with ML tools like TensorFlow or PyTorch.
The predicted salary is between 80000 - 150000 £ per year.
Machine Learning Engineer London (Hybrid)
Salary: £80,000 - £150,000 *SC eligibility required* A leading applied AI consultancy is looking for an AI/ML Engineer to join its AI & Data Science team, working on high-impact projects across national security and defence.
Youll design, build and deploy production-grade software, infrastructure and MLOps systems that use machine learning to solve complex real-world problems.
The Role Build scalable software and infrastructure for ML systems.
Deploy and operationalise machine learning models.
Work across the full ML lifecycle with data scientists and engineers.
Design technical solutions and lead project delivery.
Work directly with customers and technical/non-technical stakeholders.
Develop reusable tools and engineering best practices.
Support and mentor junior engineers.
What We're Looking For Strong Python software engineering experience.
Understanding of the machine learning lifecycle and model deployment.
Experience with Scikit-learn, Tensor Flow or Py Torch.
Knowledge of probability, statistics and ML techniques.
Hands-on experience with at least one major cloud platform.
Docker and Kubernetes experience.
Understanding of cloud architecture, security and deployment.
Strong communication skills and the ability to work in a fast-paced environment.
Why Join?
You'll work alongside experienced AI, engineering, data science and product specialists on technically challenging national security and defence projects, helping take cutting-edge machine learning from development into real-world applications.
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ML/Engineer in Ruislip employer: All The Top Bananas
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StudySmarter Expert Advice🤫
We think this is how you could land ML/Engineer in Ruislip
✨Get Involved in Data Science Meetups
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✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like ML/Engineer at All The Top Bananas.
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like All The Top Bananas.
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When you find a suitable opening like ML/Engineer at All The Top Bananas, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace ML/Engineer in Ruislip
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at All The Top Bananas, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at All The Top Bananas. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at All The Top Bananas
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at All The Top Bananas!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
