At a Glance
- Tasks: Drive innovative research in AI, focusing on text diffusion and large-scale models.
- Company: Join Google DeepMind, a leading AI lab dedicated to transformative technology.
- Benefits: Competitive salary, diverse learning opportunities, and a commitment to ethical AI.
- Other info: Collaborate with top researchers and contribute to groundbreaking projects.
- Why this job: Make a real impact in AI development and solve complex global challenges.
- Qualifications: PhD in relevant field and experience in machine learning and programming.
The predicted salary is between 70000 - 90000 £ per year.
- Minimum Qualifications
- Ph D degree in Computer Science, Electrical Engineering, a scientific discipline, or Mathematics, a related field, or equivalent practical experience.
- 2 years of experience conducting research in machine learning, evidenced by publications or prior research roles.
- Experience in programming with Python-based scientific libraries (e. g., Num Py, Sci Py, JAX, or Tensor Flow).
- Experience with language models (LLMs), transformers, diffusion models, text diffusion, or distributed training.
- Experience with machine learning, mathematics, and statistics (e. g., linear algebra or calculus).
- Preferred Qualifications
- Experience in C++ or broader programming.
- Experience in data engineering and visualization.
- Experience in large-scale system design and distributed systems.
- Strong communication skills, including experience in technical discussions, presentations, and research writing.
- A track record of building software, either in open source or as part of a company product or research papers.
- Distributed computation for ML, especially in the context of accelerators (e. g., sharding, multi-host computation).
About the Job
As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work.
As a Research Scientist, you’ll set up large‑scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies.
From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real‑world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.
As a Research Scientist, you’ll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
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 diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Responsibilities
- Drive novel and disruptive research to advance frontier AI models, particularly within text diffusion, by identifying and solving key scientific challenges.
- Prototype and develop new architectures and algorithms, contributing directly to Gemini Diffusion research efforts.
- Validate the theoretical and practical impact of research at scale through experimental design, execution, and in‑depth analysis.
- Advance the fundamental architecture, algorithmic design, and capabilities of large‑scale diffusion models.
- Collaborate with other Generative AI teams to transition research technologies into production, fostering a culture of deep scientific expertise and accuracy.
- Equal Employment Opportunity Statement
Google is proud to be an equal opportunity workplace and is an affirmative action employer.
We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
See also Google’s EEO Policy and EEO is the Law.
If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
#J-18808-Ljbffr
StudySmarter Expert Advice🤫
We think this is how you could land Research Scientist, Gemini Diffusion, DeepMind in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Google DeepMind!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Research Scientist, Gemini Diffusion, DeepMind at Google DeepMind.
✨Leverage Professional Networks
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 Google DeepMind.
✨Apply Directly through Our Website
When you find a suitable opening like Research Scientist, Gemini Diffusion, DeepMind at Google DeepMind, 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 Research Scientist, Gemini Diffusion, DeepMind 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 Google DeepMind, 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 Google DeepMind. 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 Google DeepMind
✨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 Google DeepMind!
✨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.
