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- Tasks: Join a pioneering team to enhance large-scale language models and develop innovative strategies.
- Company: Leading research and technology firm at the forefront of machine learning.
- Benefits: Competitive salary and the chance to work on cutting-edge projects.
- Why this job: Make a real impact in the world of AI and language models.
- Qualifications: PhD in relevant field and experience with LLM training pipelines.
- Other info: Full-time role based in the UK with exciting career growth opportunities.
The predicted salary is between 36000 - 60000 £ per year.
A leading research and technology firm is seeking a Machine Learning Research Engineer to join their pioneering team. You will work on large-scale language models that enhance discovery workflows, focusing on model adaptation, reasoning, and developing innovative strategies.
The ideal candidate holds a PhD and has practical experience in LLM training pipelines, along with proficiency in Python and machine learning frameworks. This is a full-time role that offers a competitive salary, primarily based in the UK.
LLM Post-Training Engineer – Advanced Reasoning & Alignment in England employer: EPM Scientific
Contact Detail:
EPM Scientific Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land LLM Post-Training Engineer – Advanced Reasoning & Alignment in England
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at 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 LLMs and machine learning. It’s a great way to demonstrate your expertise beyond the application.
✨Tip Number 3
Prepare for interviews by brushing up on common questions in the field. We recommend practising with friends or using mock interview platforms to build confidence.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities, and applying directly can sometimes give you an edge over others.
We think you need these skills to ace LLM Post-Training Engineer – Advanced Reasoning & Alignment in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the LLM Post-Training Engineer role. Highlight your experience with large-scale language models and any relevant projects you've worked on. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about advanced reasoning and alignment in machine learning. Share specific examples of your work that demonstrate your expertise and enthusiasm.
Showcase Your Technical Skills: Don’t forget to mention your proficiency in Python and any machine learning frameworks you’ve used. We’re looking for someone who can hit the ground running, so make sure we know what tools you’re comfortable with!
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. Plus, we love seeing applications come in through our own platform!
How to prepare for a job interview at EPM Scientific
✨Know Your Models
Make sure you’re well-versed in the latest advancements in large-scale language models. Brush up on your understanding of model adaptation and reasoning techniques, as these will likely be key discussion points during your interview.
✨Showcase Your Experience
Prepare to discuss your practical experience with LLM training pipelines in detail. Be ready to share specific examples of projects you've worked on, the challenges you faced, and how you overcame them. This will demonstrate your hands-on expertise.
✨Python Proficiency is Key
Since proficiency in Python is a must-have, ensure you can talk about your coding experience confidently. Consider preparing a small coding challenge or example that showcases your skills in machine learning frameworks relevant to the role.
✨Innovative Thinking
This role focuses on developing innovative strategies, so come prepared with ideas! Think about potential improvements or new approaches you could suggest for enhancing discovery workflows using LLMs. This will show your proactive mindset and creativity.
