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For Companies At a Glance
- Tasks: Design and deploy cutting-edge machine learning systems that drive real-world AI solutions.
- Company: Join a leading applied AI company in the UK with a focus on innovation.
- Benefits: Competitive salary up to £85k, remote work options, and professional growth opportunities.
- Why this job: Make a tangible impact in the financial and professional services sectors with your AI expertise.
- Qualifications: Experience in ML systems, Python proficiency, and cloud-native system design required.
- Other info: Collaborative environment with mentorship opportunities for junior engineers.
The predicted salary is between 43200 - 72000 £ per year.
Xcede has just started working with one of the leading applied AI companies in the UK. If you want to have a real impact, this is the role for you!
Build and deploy real-world AI systems that power critical decisions across major financial and professional services organisations. You will create and deliver tailored AI solutions for clients, shape resilient and extensible system architectures, partner with commercial stakeholders to define technically sound and commercially viable project strategies, and bring advanced machine learning capabilities into real-world production environments while setting high standards for the responsible design, deployment, and operation of AI systems at scale.
Responsibilities
- Design, build, deploy, and maintain machine learning systems throughout their entire operational lifecycle.
- Collaborate closely with data science teams to integrate and productionise trained ML models within live systems.
- Provide hands-on support for models built with widely used machine learning libraries.
- Develop proficiency in Python.
- Design and operate cloud-native systems, including secure infrastructure, deployment pipelines, and open-source technologies, with experience on at least one major platform (e.g., AWS).
- Build and run containerised systems using Docker and Kubernetes in production environments.
- Apply a strong grasp of fundamental probability and statistical principles.
- Mentor and provide technical leadership to junior team members through hands-on guidance.
Qualifications
- Proven ability to design, develop, deploy, and maintain ML systems across their operational lifecycle.
- Experience collaborating with data science teams to productionise ML models.
- Hands-on experience implementing and supporting models with popular ML libraries.
- Proficiency in Python.
- Experience designing and operating cloud-native systems with secure infrastructure and deployment pipelines; familiarity with major platforms (e.g., AWS).
- Experience with Docker and Kubernetes in production.
- Strong understanding of probability and statistics.
- Experience mentoring and leading junior engineers.
If you are interested in this or other ML Engineering positions, please contact Gilad Sabari.
Machine Learning Engineer (I & II) - CAS / PFS / GPS employer: Xcede Recruitment Solutions
Contact Detail:
Xcede Recruitment Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (I & II) - CAS / PFS / GPS
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow Machine Learning enthusiasts. 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 a GitHub repo 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 knowledge and be ready to discuss your past projects in detail. Practising common ML interview questions can help you feel more confident when it’s time to shine.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of exciting opportunities waiting for you. Plus, applying directly can sometimes give you a better chance of getting noticed by hiring managers.
We think you need these skills to ace Machine Learning Engineer (I & II) - CAS / PFS / GPS
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 proficiency in Python, experience with ML libraries, and any cloud-native systems you've worked on. We want to see how you can bring real-world AI solutions to life!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how your background aligns with our mission at StudySmarter. Don’t forget to mention any relevant projects or experiences that showcase your ability to design and deploy ML systems.
Showcase Your Projects: If you've worked on any interesting ML projects, make sure to include them in your application. Whether it's a personal project or something from a previous job, we love seeing practical examples of your work. It helps us understand your hands-on experience and creativity!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It streamlines the process for us and ensures your application lands in the right hands. Plus, it shows you're keen on joining the StudySmarter team!
How to prepare for a job interview at Xcede Recruitment Solutions
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts and frameworks. Be ready to discuss your experience with popular libraries and how you've implemented them in real-world projects. This will show that you can hit the ground running!
✨Showcase Your Python Skills
Since proficiency in Python is key for this role, prepare to demonstrate your coding skills. You might be asked to solve a problem or explain your code. Practise coding challenges beforehand to boost your confidence.
✨Understand Cloud-Native Systems
Familiarise yourself with cloud platforms like AWS and how to design secure infrastructure. Be prepared to discuss your experience with deployment pipelines and containerisation using Docker and Kubernetes. This knowledge will set you apart from other candidates.
✨Be Ready to Mentor
As mentoring junior engineers is part of the role, think about examples where you've provided guidance or leadership. Share your approach to helping others grow, as this shows you're not just technically skilled but also a team player.
