At a Glance
- Tasks: Train and evaluate cutting-edge LLMs while working on large-scale data pipelines.
- Company: Join White Circle, a leader in AI safety and innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Fast-paced environment with exciting challenges and career advancement potential.
- Why this job: Make a real impact on AI safety and collaborate with top engineers and researchers.
- Qualifications: Experience in ML engineering and a passion for AI safety.
The predicted salary is between 80000 - 98000 £ per year.
White Circle is hiring ML Engineers to train, post-train, and evaluate the LLMs at the core of our platform.
You will work on large-scale data pipelines, SFT/RLHF-style alignment, and distributed multi-GPU training.
The role is hands-on with rapid deployment to production, impacting how AI safety is built.
You will collaborate with engineering and research to ensure latency, cost, and privacy constraints are met while delivering actionable insights to product and operations.
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StudySmarter Expert Advice🤫
We think this is how you could land LLM Safety ML Engineer - Training, Evaluation & Scale in London
✨Get Involved in Data Science Meetups
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✨Apply Directly through Our Website
When you find a suitable opening like LLM Safety ML Engineer - Training, Evaluation & Scale at White Circle, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace LLM Safety ML Engineer - Training, Evaluation & Scale 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!
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Craft a Tailored Cover Letter:For a full-time role at White Circle, 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 White Circle. 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 White Circle
✨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 White Circle!
✨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.