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- Tasks: Design systems for high-impact research using cutting-edge machine learning technologies.
- Company: Leading data science firm in London with a focus on innovation.
- Benefits: Highly competitive compensation, excellent work-life balance, and generous benefits.
- Why this job: Join a dynamic team and shape the future of machine learning in research.
- Qualifications: Postgraduate degree in machine learning or relevant experience with strong engineering skills.
- Other info: Collaborative environment with opportunities to work across various disciplines.
The predicted salary is between 43200 - 72000 £ per year.
A leading data science firm in London seeks an exceptional Machine Learning Engineer to work in the ML and HPC Architecture team. You will design systems that drive high-impact research and collaborate across various disciplines to leverage next-generation machine learning technologies.
Candidates should possess a postgraduate degree in machine learning or relevant experience, with strong object-oriented engineering skills and a passion for the latest trends.
The role offers highly competitive compensation, excellent work-life balance, and generous benefits.
ML Engineer for Scalable HPC & Quant Research in London employer: G-Research
Contact Detail:
G-Research Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer for Scalable HPC & Quant Research in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the ML and HPC fields on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and high-performance computing. This gives us a tangible way to see what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your object-oriented programming skills. We love candidates who can demonstrate their coding prowess and problem-solving abilities on the spot.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate individuals ready to make an impact.
We think you need these skills to ace ML Engineer for Scalable HPC & Quant Research in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning and HPC. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or technologies you've worked with!
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 you can contribute to our team. We love seeing enthusiasm and a clear understanding of the role.
Showcase Your Projects: If you’ve got any personal or professional projects that demonstrate your skills in ML or HPC, include them! We appreciate candidates who can show us their hands-on experience and innovative thinking.
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 G-Research
✨Know Your ML Fundamentals
Brush up on your machine learning concepts and algorithms. Be ready to discuss how you’ve applied these in past projects, especially in scalable HPC environments. This shows you’re not just familiar with theory but can also implement it effectively.
✨Showcase Your Engineering Skills
Prepare to demonstrate your object-oriented programming skills. Bring examples of your code or projects that highlight your engineering prowess. This will help the interviewers see your technical capabilities in action.
✨Stay Updated on Trends
Familiarise yourself with the latest trends in machine learning and high-performance computing. Being able to discuss recent advancements or technologies will show your passion for the field and your commitment to continuous learning.
✨Collaborative Mindset
Since the role involves collaboration across various disciplines, be prepared to discuss how you’ve worked in teams before. Share specific examples of how you’ve successfully collaborated with others to achieve a common goal, highlighting your communication skills.
