At a Glance
- Tasks: Design experiments and build infrastructure for cutting-edge AI research.
- Company: Join DeepMind, a leader in AI innovation based in London.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on groundbreaking technology.
- Why this job: Be at the forefront of AI research and make a significant impact.
- Qualifications: Experience in AI research and strong analytical skills.
The predicted salary is between 60000 - 80000 £ per year.
Deep Mind in London, UK, is seeking a Research Scientist (Post-Training) or Research Engineer to push the frontier of agentic tasks in post-training LLMs.
You will design scalable experiments and build infrastructure for tool use and RL in Gemini post-training.
You will lead from hypothesis to impact, collaborate with researchers and engineers, and communicate results through clear plots and reports.
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Agent Post-Training Research Scientist — RL & AI in London employer: Software Careers
Elastic is an exceptional employer that fosters a collaborative and inclusive work culture, particularly for the Principal Software Engineer role in London. With a strong emphasis on employee growth and development, the company provides competitive benefits and encourages innovation in enhancing search capabilities. Working remotely with a diverse team allows for meaningful contributions to cutting-edge technology while enjoying a supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Agent Post-Training Research Scientist — RL & AI in London
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Software Careers.
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We think you need these skills to ace Agent Post-Training Research Scientist — RL & AI 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 Software Careers, 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 Software Careers. 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 Software Careers
✨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 Software Careers!
✨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.
