At a Glance
- Tasks: Join Google DeepMind to develop prototypes and scale algorithms for groundbreaking research projects.
- Company: Be part of a leading tech company at the forefront of AI innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with endless opportunities to learn and grow.
- Why this job: Make a real impact in AI research while collaborating with top experts in the field.
- Qualifications: Strong software engineering skills, especially in Python or C++, and a passion for machine learning.
The predicted salary is between 60000 - 80000 £ per year.
The role We are looking for Research Engineers to expand our team at Google DeepMind. As a Research Engineer you will work directly on a wide range of research projects, in collaboration with Research Scientists and Software Engineers. You will apply your engineering and research skills to accelerate research progress through developing prototypes, scaling up algorithms, overcoming technical obstacles, and designing, running, and analysing experiments.
Key responsibilities include:
- Develop research or product prototypes, generating research ideas and collaboratively iterating on their improvement, e.g. by reading and reproducing existing papers, identifying and applying key insights in new contexts, or combining them in novel ways.
- Perform and analyze experiments, and scale up experimentally successful algorithms.
- Build tools and infrastructure in support of research projects, e.g. by surveying the technical landscape, identifying and deploying suitable existing tools, or designing new solutions.
- Act as a bridge between research and engineering, bringing engineering expertise into research projects and research experience into engineering of tools and frameworks.
- Collaborate and communicate ideas, plans and outcomes (orally and in writing) within projects and with adjacent teams, aligning work and timelines with affected teams, sharing insights and reviewing others' work to achieve milestones.
- Champion engineering standard methodologies within and around the team, e.g. by improving workflows, promoting code reviews, mentoring on code readability, etc.
- Propose direction and advise on projects according to your individual experience and expertise.
- Proactively share your individual skills and knowledge, and collaboratively upskill adjacent engineers and researchers.
About you
In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:
- Strong software engineering fundamentals, including fluency in Python and/or C++.
- Experience of ML/scientific libraries such as JAX, PyTorch, TensorFlow, NumPy, …
- Knowledge of mathematics, statistics and machine learning concepts needed to understand research papers and processes in the field.
- Ability to collaborate and communicate technical ideas effectively with colleagues, e.g. through discussions, whiteboard sessions, written documentation, and presentations.
In addition, the following would be an advantage:
- Machine learning and research experience in industry, academia and personal projects, whether in computer science or other fields such as physics, computational biology, or mathematics.
- Experience with Deep RL research.
- Experience with machine learning at scale; understanding of multi-accelerator multi-host distributed computation for large models.
- Experience with large scale system design.
Research Engineer, Discovery Team employer: Google DeepMind
At Google DeepMind, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. As a Research Engineer in our Discovery Team, you will have the opportunity to work alongside leading experts in the field, contributing to groundbreaking research while enjoying a supportive environment that encourages professional growth and development. Our London location offers a vibrant atmosphere, with access to cutting-edge resources and a diverse community, making it an ideal place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Research Engineer, Discovery Team
✨Tip Number 1
Network like a pro! Reach out to folks in your field on LinkedIn or at meetups. We can’t stress enough how important it is to connect with people who are already in the industry; they might just know about opportunities that aren’t advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and research. We love seeing what you can do, so make sure to highlight any prototypes or experiments you've worked on.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. We recommend practicing coding challenges and discussing your past projects. Be ready to explain your thought process and how you tackle challenges.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always looking for passionate individuals who want to join our team and contribute to exciting research projects.
We think you need these skills to ace Research Engineer, Discovery Team
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Research Engineer role. Highlight your experience with Python, C++, and any relevant ML libraries. We want to see how your skills align with our projects!
Showcase Your Projects:Include examples of your past work, especially any prototypes or experiments you've developed. We love seeing how you've tackled technical challenges and what insights you've gained from your research.
Communicate Clearly:When writing your application, be clear and concise. Use straightforward language to explain your ideas and experiences. Remember, we value effective communication just as much as technical skills!
Apply Through Our Website:Don’t forget to submit your application through our official website. It’s the best way for us to receive your details and ensure you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at Google DeepMind
✨Know Your Research
Before the interview, dive deep into recent research papers relevant to the role. Familiarise yourself with key concepts and findings, especially those related to machine learning and algorithms. This will not only help you answer questions confidently but also show your genuine interest in the field.
✨Showcase Your Projects
Be ready to discuss your past projects, particularly those involving Python or C++. Highlight how you tackled challenges, developed prototypes, and collaborated with others. Use specific examples to illustrate your problem-solving skills and technical expertise.
✨Communicate Clearly
Practice explaining complex technical ideas in simple terms. During the interview, focus on clear communication, whether you're discussing your experience or answering questions. This will demonstrate your ability to bridge the gap between research and engineering effectively.
✨Ask Insightful Questions
Prepare thoughtful questions about the team’s current projects, challenges they face, or their approach to collaboration. This shows that you’re not just interested in the position but also in contributing to the team's success and understanding their work environment.
