At a Glance
- Tasks: Drive groundbreaking research in AI and design scalable experiments for large language models.
- Company: Join Google DeepMind, a pioneering AI lab with a unique culture.
- Benefits: Competitive salary, diverse learning opportunities, and a focus on ethics and safety.
- Other info: Dynamic environment with various career pathways and exceptional team support.
- Why this job: Be at the forefront of AI innovation and make a real-world impact.
- Qualifications: Experience in research or engineering, with a passion for AI and collaboration.
The predicted salary is between 63000 - 77000 £ per year.
hackajob is collaborating with
Google to connect them with exceptional professionals for this role.
At Google Deep Mind, we've built a unique culture and work environment where long-term ambitious research can flourish.
In this role, you will push the frontier of agentic tasks in post-training large language models as a Research Scientist or Research Engineer (we are open to both).
As part of the Gemini post-training team, you will have the chance to drive the research that makes up the backbone of upcoming releases.
You will help bridge research and engineering by designing scalable experiments and building reliable infrastructure for tool use and reinforcement learning.
You will value various experience and backgrounds to create extraordinary impact.
Artificial intelligence will be one of humanity’s most transformative inventions.
At Google Deep Mind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users.
We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
We are pushing the boundaries across multiple domains.
Our global teams offer various learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
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Research Scientist, Agent Post-Training, DeepMind employer: hackajob
At hackajob, we pride ourselves on being an exceptional employer that fosters a culture of innovation and inclusivity. Our diverse team thrives in a high-performance environment where your contributions directly impact our multi-asset platform's success. With ample opportunities for professional growth and a commitment to employee development, joining us means being part of a forward-thinking company that values your expertise and ambition.
StudySmarter Expert Advice🤫
We think this is how you could land Research Scientist, Agent Post-Training, DeepMind
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Research Scientist, Agent Post-Training, DeepMind
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 hackajob, 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 hackajob. 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 hackajob
✨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!
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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 hackajob!
✨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.
