At a Glance
- Tasks: Run cutting-edge research methods and optimise performance with large-scale compute.
- Company: Join Google DeepMind, a pioneering AI lab focused on transformative technology.
- Benefits: Enjoy competitive salary, diverse learning opportunities, and a commitment to ethics and safety.
- Other info: Collaborate with top researchers and explore varied career pathways in a dynamic environment.
- Why this job: Make a real impact in AI development while contributing to the global research community.
- Qualifications: Bachelor's degree in relevant field and experience with Python-based scientific libraries.
The predicted salary is between 60000 - 80000 £ per year.
- Minimum Qualifications
- Bachelor's degree in computer science, electrical engineering, science, mathematics or equivalent experience.
- 2 years of experience in programming, specifically with Python-based scientific libraries such as JAX, Py Torch, Tensor Flow, Num Py.
- Experience in developing or implementing machine learning models in a production or research environment.
- Preferred Qualifications
- Experience with large-scale system design, distributed systems.
- Experience in data engineering and visualisation.
- C++ or broader programming experience.
- Academic research experience in machine learning, publications, or research experience in related fields.
- Knowledge of distributed computation for ML, especially in the context of accelerators (e. g. sharding, multi-host computation).
- Strong communication skills (via discussion, presentation, technical and research writing, whiteboarding).
About the job
At Google, research-focused Software Engineers are embedded throughout the company, allowing them to set up large-scale tests and deploy promising ideas quickly and broadly.
Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.
But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.
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.
Responsibilities
- Determine how to run research methods with large-scale compute.
- Optimize performance through engineering and benchmarking.
- Solve key research challenges by designing and running experiments, sharing analyses and proposing next steps.
- Integrate engineering expertise into research projects, sharing skills and knowledge with other engineers and researchers.
- Design, build, and improve infrastructure for research.
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.
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StudySmarter Expert Advice🤫
We think this is how you could land Research Engineer, Continual Learning, DeepMind in London
✨Get Involved in Data Science Communities
Join online platforms like Kaggle, GitHub, or local meetups focused on data science. Contributing to open-source projects or competing in data challenges can really boost your visibility and showcase your skills to potential employers like Google DeepMind.
✨Utilise University Career Services
Tap into your university’s career services for internships or early-talent programmes specifically tailored for data science students. They often have connections with companies like Google DeepMind who are on the lookout for fresh talent, so don’t miss out on those opportunities!
✨Show Off Your Projects
Create a portfolio that highlights your data analysis projects, especially any real-world applications. Sharing your projects on platforms like GitHub or even a personal website allows recruiters at places like Google DeepMind to see what you can achieve beyond your degree.
✨Be Active on LinkedIn
Don’t just use LinkedIn to connect; share your insights on data trends or engage with posts from industry leaders. This can really help you stand out when applying for roles at companies like Google DeepMind.
We think you need these skills to ace Research Engineer, Continual Learning, DeepMind in London
Some tips for your application 🫡
Show Off Your Technical Skills!:When applying for a data science internship like the one at Google DeepMind, make sure your CV highlights relevant technical skills such as programming languages (like Python or R), data visualisation tools, and statistical analysis. Include projects or coursework that illustrate your hands-on experience with these skills—this grabs our attention!
Include Your Side Projects:Data science is all about practical application, so don’t be shy about showcasing any side projects or personal initiatives—like a cool data analysis you did or a Kaggle competition you joined. This is the perfect way to demonstrate your passion for the field and your ability to apply what you’ve learnt.
Craft an Engaging Cover Letter:This isn’t just another application; it’s your chance to tell us why you’re all about data science! In your cover letter, reflect on why this internship excites you and how it fits into your learning journey. Let us see your enthusiasm and potential for growth in this field—it's a huge plus!
Keep It Clean and Professional:While we love creativity, keeping your CV and cover letter clear and professional is super important. Make sure they're easy to read with a nice layout. Use bullet points to highlight key achievements—this makes it easier for us to find the juicy bits quickly. And seriously, don’t forget to apply through our website!
How to prepare for a job interview at Google DeepMind
✨Master the Tech Stack
As we're diving into data science for an internship level, brush up on the key tools and languages like Python, R, and SQL. You might be asked to demonstrate your knowledge through practical coding exercises, so ensure you can confidently run through basic algorithms or data manipulation tasks during your interview.
✨Portfolio Power
Make sure your portfolio shines! Bring examples of projects you've worked on, showcasing your data analysis and visualisation skills. Especially for an internship, having real-world applications of your coursework or personal projects can really set you apart and spark great conversations.
✨Explain Your Thought Process
Data science isn't just about crunching numbers; it's about communicating insights too. Prepare to explain your methodologies clearly. For instance, if asked about a project, outline how you approached the problem, what data you collected, and what insights you derived. This shows your analytical thinking and problem-solving skills.
✨Show Your Curiosity
For a bachelor's level position, the interviewers will be keen to see your enthusiasm and willingness to learn. Think of ways to discuss how you stay updated with the latest trends in data science or any online courses you've taken. This reflects not just your technical skills, but your passion for the field, which is crucial for an internship position.
