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- Tasks: Drive innovation in AI model architecture and enhance intelligence with cutting-edge techniques.
- Company: Join a leading AI research team focused on groundbreaking advancements.
- Benefits: 100% remote work, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with access to thousands of NVIDIA GPUs for large-scale training.
- Why this job: Make a real impact in the AI field while working with state-of-the-art technologies.
- Qualifications: Degree in Computer Science or related field; PhD preferred with strong AI R&D background.
The predicted salary is between 70000 - 90000 £ per year.
As a member of the AI model team, you will drive innovation in architecture development for cutting‑edge models of various scales, including small, large, and multi‑modal systems. Your work will enhance intelligence, improve efficiency, and introduce new capabilities to advance the field.
You will have a deep expertise in LLM architectures, a strong grasp of pre‑training optimization with a hands‑on, research‑driven approach. Your mission is to explore and implement novel techniques and algorithms that lead to groundbreaking advancements: data curation, strengthening baselines, identifying and resolving existing pre‑training bottlenecks to push the limits of AI performance.
Responsibilities- Conduct pre‑training AI models on large, distributed servers equipped with thousands of NVIDIA GPUs.
- Design, prototype, and scale innovative architectures to enhance model intelligence.
- Independently and collaboratively execute experiments, analyze results, and refine methodologies for optimal performance.
- Investigate, debug, and improve both model efficiency and computational performance.
- Contribute to the advancement of training systems to ensure seamless scalability and efficiency on target platforms.
- A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).
- Hands‑on experience contributing to large‑scale LLM training runs on large, distributed servers equipped with thousands of NVIDIA GPUs, ensuring scalability and impactful advancements in model performance.
- Familiarity and practical experience with large‑scale, distributed training frameworks, libraries and tools.
- Deep knowledge of state‑of‑the‑art transformer and non‑transformer modifications aimed at enhancing intelligence, efficiency and scalability.
- Strong expertise in PyTorch and Hugging Face libraries with practical experience in model development, continual pretraining, and deployment.
AI Research Engineer Pre training 100% Remote employer: Framework Ventures
Contact Detail:
Framework Ventures Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Research Engineer Pre training 100% Remote
✨Tip Number 1
Network like a pro! Reach out to folks in the AI community, attend meetups or webinars, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to LLM architectures and pre-training optimisation. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for interviews by brushing up on the latest trends in AI and machine learning. Be ready to discuss your past experiences and how they relate to the role. Practice common technical questions to boost your confidence!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace AI Research Engineer Pre training 100% Remote
Some tips for your application 🫡
Show Off Your Expertise: Make sure to highlight your deep expertise in LLM architectures and pre-training optimisation. We want to see how your hands-on, research-driven approach can drive innovation in our AI model team!
Tailor Your Application: Don’t just send a generic application! Tailor your CV and cover letter to reflect the specific skills and experiences that match the job description. We love seeing how you can contribute to enhancing model intelligence and efficiency.
Be Clear and Concise: When writing your application, keep it clear and concise. We appreciate straightforward communication that gets to the point while showcasing your achievements and relevant experience in AI R&D.
Apply Through Our Website: Remember to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to push the limits of AI performance.
How to prepare for a job interview at Framework Ventures
✨Know Your Stuff
Make sure you brush up on the latest advancements in AI and LLM architectures. Be ready to discuss your hands-on experience with large-scale training runs and how you've tackled pre-training bottlenecks in the past.
✨Showcase Your Projects
Prepare to talk about specific projects you've worked on, especially those involving PyTorch and Hugging Face. Highlight any innovative architectures you've designed or prototyped, and be ready to explain the impact of your work.
✨Be Ready for Technical Questions
Expect deep technical questions related to model efficiency and computational performance. Brush up on your knowledge of distributed training frameworks and be prepared to discuss how you've improved model scalability in previous roles.
✨Collaborative Mindset
Since the role involves both independent and collaborative work, be ready to share examples of how you've successfully executed experiments in a team setting. Emphasise your ability to analyse results and refine methodologies together with others.