At a Glance
- Tasks: Deploy and maintain machine learning models in a fast-paced, innovative environment.
- Company: Join a leading firm in financial services, driving AI research and solutions.
- Benefits: Enjoy remote work flexibility and a collaborative, dynamic culture.
- Other info: Work in Agile teams and contribute to impactful projects until 31/07/2025.
- Why this job: Be at the forefront of AI, solving real-world problems with cutting-edge technology.
- Qualifications: Passion for AI, STEM background, and experience with machine learning tools required.
The predicted salary is between 36000 - 60000 € per year.
Join us as a Machine Learning Engineer
- We\'re looking for someone to deploy, automate, maintain and monitor machine learning models and algorithms to make sure they work effectively in a production environment
- Day-to-day, you\'ll be at the forefront of applied AI and AI research in the financial services industry, collaborating with talented data engineers to create innovative, data-driven solutions and productionize machine learning models
- This is your opportunity to turn your interests into a diverse and rewarding career, as you solve new problems and create smarter solutions in a non-stop innovation environment
Your daily responsibilities will see you codifying and automating machine learning model production, including pipeline optimisation, tuning and fault finding, as well as transforming data science prototypes and applying appropriate machine learning algorithms and tools.
We\'ll need you to deploy and maintain adopted end-to-end solutions, including building metrics to improve system performance and identifying and resolving differences in data distribution which affect model performance. You\'ll also maintain knowledge of data science and machine learning.
In addition, you\'ll be responsible for:
- Understanding the needs of our business stakeholders, and how machine learning solutions meet those needs to support the achievement of our business strategy
- Productionising machine learning models, including pipeline design, development, testing, and deployment, ensuring the original intent is carried over to production
- Creating frameworks to make sure the monitoring of machine learning models within the production environment is robust
- Delivering models that adhere to expected quality and performance while understanding and addressing any shortfalls, for example through retraining
- Working in an Agile way within multi-disciplinary data and the analytics teams to achieve agreed project and Scrum outcomes
To be successful in this role, you\'ll have a passion for staying current with AI research and a desire to contribute to the field, as well as an academic background in a STEM discipline, like Mathematics, Physics, Engineering or Computer Science. You\'ll need experience with machine learning on large datasets and an understanding of machine learning approaches and algorithms.
Alongside this, you\'ll have experience of building, testing, supporting and deploying machine learning models into a production environment, using modern CI/CD tools, including Git, AWS, AWS Sagemaker, Docker, Terraform, Cloud Formation, Kubernetes, PyTorch, TensorFlow, Numpy and Scikit-learn.
Furthermore, you\'ll need:
- Strong experience of using programming and scripting languages, such as Python
- An understanding of how to synthesise, translate and visualise data and insights for key stakeholders
- Financial services knowledge and the ability to identify wider business impacts, risks and opportunities to make connections across key outputs and processes
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Job Posting Closing Date:
31/07/2025
Ways of Working:Remote First #J-18808-Ljbffr
Machine Learning Engineer employer: NatWest Group
As a leading player in the financial services industry, we offer Machine Learning Engineers a dynamic and innovative work environment where creativity and technical expertise thrive. Our remote-first culture promotes flexibility and work-life balance, while our commitment to employee growth ensures access to continuous learning opportunities and cutting-edge projects. Join us to be part of a collaborative team that values your contributions and empowers you to make a meaningful impact through advanced AI solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning and AI, especially in the financial services sector. This will not only help you understand the challenges we face but also allow you to discuss relevant topics during interviews.
✨Tip Number 2
Showcase your experience with CI/CD tools like Git, AWS, and Docker by working on personal projects or contributing to open-source initiatives. This hands-on experience can be a great talking point in interviews.
✨Tip Number 3
Network with professionals in the field through platforms like LinkedIn or local meetups. Engaging with others can provide insights into the role and may even lead to referrals for positions at StudySmarter.
✨Tip Number 4
Prepare to discuss how you've applied machine learning algorithms in real-world scenarios. Be ready to explain your thought process and the impact of your work, as this demonstrates your ability to translate technical skills into business value.
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, particularly with large datasets and production environments. Emphasise your familiarity with tools like AWS, Docker, and Python, as these are crucial for the role.
Craft a Compelling Cover Letter:In your cover letter, express your passion for AI and machine learning. Discuss specific projects or experiences that demonstrate your ability to deploy and maintain machine learning models, and how you can contribute to the company's goals.
Showcase Relevant Skills:Clearly outline your technical skills related to machine learning algorithms, CI/CD tools, and programming languages. Use examples to illustrate your proficiency and how you've applied these skills in previous roles.
Highlight Collaboration Experience:Since the role involves working with multi-disciplinary teams, mention any past experiences where you collaborated with data engineers or other stakeholders. This will show your ability to work effectively in an Agile environment.
How to prepare for a job interview at NatWest Group
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning algorithms and tools. Highlight specific projects where you've deployed models in a production environment, and be ready to explain the challenges you faced and how you overcame them.
✨Understand the Business Context
Demonstrate your understanding of how machine learning solutions can support business strategies. Research the company’s goals and think about how your skills can help achieve them, especially in the financial services sector.
✨Prepare for Problem-Solving Questions
Expect to face technical questions that assess your problem-solving abilities. Practice explaining your thought process when optimising pipelines or addressing model performance issues, as this will showcase your analytical skills.
✨Familiarise Yourself with Agile Methodologies
Since the role involves working in an Agile environment, brush up on Agile principles and practices. Be ready to discuss your experience working in cross-functional teams and how you contribute to achieving project outcomes.
