At a Glance
- 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 impactful projects.
- Why this job: Be at the forefront of AI technology and make a real impact in the field.
- Qualifications: Degree in Computer Science or related field; PhD preferred with AI R&D experience.
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.
Qualifications:
- 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 in London employer: Framework Ventures
As a leading innovator in AI research, our company offers a dynamic and collaborative work environment that empowers AI Research Engineers to push the boundaries of technology from the comfort of their own homes. With a strong focus on employee growth, we provide access to cutting-edge resources and opportunities for professional development, ensuring that our team members are at the forefront of advancements in AI. Join us to be part of a forward-thinking culture that values creativity, innovation, and the pursuit of excellence in the rapidly evolving field of artificial intelligence.
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We think this is how you could land AI Research Engineer Pre training 100% Remote in London
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We think you need these skills to ace AI Research Engineer Pre training 100% Remote in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Framework Ventures, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Framework Ventures. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Framework Ventures
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Framework Ventures!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
