Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and train cutting-edge generative models while managing deep learning infrastructure.
- Company: Leading technology recruitment agency in the heart of London.
- Benefits: Competitive salary and a dynamic work environment.
- Why this job: Join a pioneering team and shape the future of machine learning.
- Qualifications: 3+ years in deep learning, Python mastery, and experience with PyTorch or JAX.
- Other info: Exciting opportunity for career growth in a vibrant tech scene.
The predicted salary is between 48000 - 84000 £ per year.
A leading technology recruitment agency is seeking a Senior Machine Learning Research Engineer in London. The role requires designing and training state-of-the-art generative models while managing deep learning infrastructure.
Candidates should possess:
- 3+ years of experience in deep learning
- Mastery of Python
- Familiarity with frameworks like PyTorch or JAX
This full-time position requires hands-on experience with LLMs or diffusion models and adherence to modern software engineering practices, with a competitive compensation package offered.
Senior ML Research Engineer — On-site in London employer: Randstad Digital
Contact Detail:
Randstad Digital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Research Engineer — On-site in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech industry, especially those who work with machine learning. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving generative models or deep learning. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and frameworks like PyTorch or JAX. Practice coding challenges and be ready to discuss your past projects in detail—this is your chance to shine!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented folks like you. Plus, it’s a great way to ensure your application gets noticed by the right people.
We think you need these skills to ace Senior ML Research Engineer — On-site in London
Some tips for your application 🫡
Show Off Your Experience: Make sure to highlight your 3+ years of experience in deep learning. We want to see how you've tackled challenges and what projects you've worked on, especially if they involve generative models or LLMs.
Be Specific About Your Skills: When mentioning your Python skills, don't just say you're proficient. Tell us about the frameworks you’ve used, like PyTorch or JAX, and any specific projects where you applied them. We love details!
Demonstrate Your Problem-Solving Skills: In your application, share examples of how you've managed deep learning infrastructure or solved complex problems. This shows us that you can think critically and adapt to new challenges.
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 Randstad Digital
✨Know Your Models
Make sure you brush up on the latest generative models, especially LLMs and diffusion models. Be ready to discuss your hands-on experience with these technologies and how you've applied them in past projects.
✨Showcase Your Python Skills
Since mastery of Python is crucial for this role, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice coding challenges that involve deep learning concepts.
✨Familiarise with Frameworks
Get comfortable with PyTorch or JAX, as these are key frameworks for the position. Consider building a small project or two using these tools to showcase your practical knowledge during the interview.
✨Discuss Software Engineering Practices
Be prepared to talk about modern software engineering practices you've implemented in your work. This could include version control, testing, and deployment strategies, which are essential for managing deep learning infrastructure.
