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- Tasks: Design, build, and deploy machine learning models for engineering software.
- Company: Global software company focused on applied AI and high-performance tools.
- Benefits: Competitive salary, bonus, unrivalled benefits, and hands-on experience.
- Other info: Collaborate with experts and influence global software products.
- Why this job: Tackle real-world engineering challenges with cutting-edge AI technology.
- Qualifications: Strong Python skills and experience with ML in real-world applications.
The predicted salary is between 50000 - 65000 £ per year.
A global software company is evolving its core engineering platforms by embedding machine learning and applied AI into high-performance simulation and modelling tools used worldwide. This is a hands-on applied AI role focused on building and deploying ML solutions inside production-grade engineering systems, not isolated research or experimental prototypes.
You’ll design, build, and deploy machine learning models that directly enhance complex engineering software products. Expect a blend of ML engineering, software development, and computational problem solving. You’ll work across the full ML lifecycle, ensuring models are not only accurate, but efficient, scalable, and production-ready.
Key Responsibilities- Build and deploy ML models into production engineering software systems
- Own the full ML pipeline: data prep, feature engineering, training, evaluation, optimisation
- Translate complex scientific/engineering problems into ML-driven solutions
- Improve model performance in compute-intensive environments
- Write clean, testable, maintainable production code
- Integrate ML services via APIs and software components
- Collaborate with engineers and domain specialists on real-world systems
- Strong Python programming and software engineering fundamentals
- Proven experience applying ML to real-world datasets and problems
- Understanding of model trade-offs, performance, and production constraints
- Experience working with complex or imperfect data (not just curated datasets)
- Ability to write efficient, scalable, production-quality code
- PyTorch, TensorFlow, or similar ML frameworks
- Scientific computing / numerical methods / optimisation
- GPU acceleration or high-performance computing
- MLOps, model deployment, APIs, or production pipelines
- Focus on applied AI in real engineering systems
- Work on technically challenging, high-impact problems
- Close collaboration with experienced engineers and domain experts
- Influence how AI is embedded into core global software products
- Long-term technical depth, not short-cycle ML experimentation
Please send a copy of your CV to apply or call us for an informal chat. Thanks.
Machine Learning Engineer (Applied AI / Scientific Computing) in London employer: Ion recruitment
Contact Detail:
Ion recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (Applied AI / Scientific Computing) in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the machine learning and AI space on LinkedIn. Join relevant groups, attend meetups, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it’s GitHub repos or a personal website, having tangible examples of your work can really set you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical skills and be ready to discuss your past projects in detail. Practice common ML interview questions and coding challenges to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Machine Learning Engineer (Applied AI / Scientific Computing) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and ML frameworks like PyTorch or TensorFlow. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Showcase Real-World Experience: When detailing your past roles, focus on how you've applied ML to real-world datasets. We’re looking for practical applications, not just theoretical knowledge, so share those success stories!
Keep It Clean and Concise: Your application should be easy to read and straight to the point. Use clear language and avoid jargon where possible. We appreciate a well-structured CV that gets to the heart of your qualifications quickly.
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 Ion recruitment
✨Know Your ML Fundamentals
Brush up on your machine learning fundamentals, especially around model performance and production constraints. Be ready to discuss how you've applied ML to real-world datasets and the trade-offs you've encountered.
✨Showcase Your Coding Skills
Since this role requires strong Python programming, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice writing clean, testable code that reflects your software engineering fundamentals.
✨Understand the Full ML Lifecycle
Familiarise yourself with the entire ML pipeline from data preparation to model deployment. Be prepared to discuss specific examples of how you've owned this process in past projects, particularly in compute-intensive environments.
✨Collaborate and Communicate
This position involves working closely with engineers and domain specialists. Think of examples where you've successfully collaborated on complex problems and be ready to share how you communicate technical concepts to non-technical team members.