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- Tasks: Design and train machine learning models on complex datasets for exciting client projects.
- Company: Leading data and analytics consultancy based in Greater London.
- Benefits: Remote work, flexible hours, and opportunities for professional growth.
- Other info: Engage with clients while enjoying a hybrid working model.
- Why this job: Join a dynamic team and make an impact with cutting-edge AI technology.
- Qualifications: 3+ years in ML engineering, proficient in Python, SQL, and modern ML frameworks.
The predicted salary is between 42000 - 84000 £ per year.
A leading data and analytics consultancy in Greater London is looking for a Machine Learning Engineer to design, train, and productionise ML models on complex datasets. This role involves designing predictive models, owning data flows, and integrating advanced AI components within client projects.
The ideal candidate will have over 3 years of experience in ML engineering and be skilled in Python, SQL, and modern ML frameworks. A hybrid working model with some client engagement is expected.
Machine Learning Engineer — Remote & Flexible Hours employer: Xantura Limited
Contact Detail:
Xantura Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer — Remote & Flexible Hours
✨Tip Number 1
Network like a pro! Reach out to professionals in the machine learning field on LinkedIn or attend industry meetups. You never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those involving Python and SQL. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common ML concepts and frameworks. Practice explaining your past projects and how you tackled challenges—confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that match your skills, and applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Machine Learning Engineer — Remote & Flexible Hours
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with Python, SQL, and any ML frameworks you've worked with. We want to see how you’ve tackled complex datasets and what predictive models you’ve designed.
Tailor Your Application: Don’t just send a generic CV! Customise your application to reflect the specific requirements of the Machine Learning Engineer role. We love seeing how your unique experiences align with our needs.
Be Clear and Concise: When writing your cover letter or personal statement, keep it straightforward. We appreciate clarity, so get to the point about why you’re the perfect fit for this role without fluff.
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 don’t miss out on any important updates from us!
How to prepare for a job interview at Xantura Limited
✨Know Your ML Models Inside Out
Make sure you can discuss various machine learning models and their applications. Be prepared to explain how you've designed, trained, and deployed models in past projects, as this will show your hands-on experience.
✨Brush Up on Python and SQL
Since the role requires strong skills in Python and SQL, review key concepts and be ready to solve coding problems on the spot. Practising common algorithms and data manipulation tasks can really help you shine during technical assessments.
✨Understand the Business Context
Research the consultancy's clients and the industries they operate in. Being able to relate your technical skills to real-world business problems will demonstrate your ability to integrate advanced AI components effectively.
✨Prepare for Client Engagement Scenarios
As the role involves some client interaction, think about how you would communicate complex technical concepts to non-technical stakeholders. Practising clear and concise explanations can set you apart from other candidates.