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- Tasks: Join a mission-driven team to tackle challenging machine learning problems and enhance Google products.
- Company: Be part of Google DeepMind, a community dedicated to solving intelligence for public benefit.
- Benefits: Enjoy a supportive environment with collaboration, learning opportunities, and a focus on innovation.
- Why this job: Make a real impact in AI while working on exciting projects like SynthID and more.
- Qualifications: Ph.D. in Computer Science or related field, programming skills, and a passion for safe machine learning.
- Other info: Diversity is valued; we encourage applicants from all backgrounds to apply.
The predicted salary is between 28800 - 48000 ÂŁ per year.
Accelerate research and product deployment in strategic projects that enable trustworthy, robust and reliable machine learning with a group of research scientists and engineers on a mission-driven team. Together, you will apply ML and other computational techniques to a wide range of challenging problems and help bring them to a wide range of Google products. A public example of recent work is SynthID, and we are actively pursuing other exciting projects across many disciplines.
About Us: We’re a dedicated scientific community, committed to “solving intelligence” and ensuring our technology is used for widespread public benefit. We’ve built a supportive and inclusive environment where collaboration is encouraged and learning is shared freely. We don’t set limits based on what others think is possible or impossible. We drive ourselves and inspire each other to push boundaries and achieve ambitious goals.
The Role: As a Research Engineer in Strategic Initiatives, you will use your machine learning expertise to collaborate with domain experts, machine learning scientists and engineers within our strategic initiatives programs and across Google. Domains may include, but are not limited to, machine learning robustness, provenance of synthetic media, and the trustworthiness of data.
- Engage with existing research efforts in the Strategic Initiatives Program to solve key challenges using your broad machine learning experience.
- Collaborate with researchers and engineers to identify and develop novel machine learning approaches and transform them to scalable solutions that can be integrated within Google products.
- Engage with product teams to drive the deployment of our research.
- Report and present research findings and developments (including status and results) clearly and efficiently both internally and externally, verbally and in writing.
- Suggest and engage in team collaborations to meet research goals for the wider science programme.
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:
- Ph.D. in Computer Science or related quantitative field or equivalent practical experience.
- Passion for accelerating the development of safe machine learning using innovative technologies.
- Programming experience.
- Quantitative skills in maths and statistics.
- Experience with common scripting languages and pipelining tools.
In addition, the following would be an advantage:
- Experience in applying machine learning techniques to problems surrounding robust and trustworthy deployments of models.
- Experience with GenAI audio or video models.
- Demonstrated success in delivering high quality research impact.
- Experience with adversarial robustness, data influence or watermarking.
- A real passion for AI!
In assessing technical backgrounds, we will take a holistic view of the mix of scientific, machine learning, and computational experience. We do not expect you to be an expert in all fields simultaneously. At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact.
We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.
Applications close at 5pm (UK) on Monday 2nd June 2024.
Research Engineer, Provenance employer: Google DeepMind
Contact Detail:
Google DeepMind Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Engineer, Provenance
✨Tip Number 1
Familiarise yourself with recent projects like SynthID and other initiatives at Google DeepMind. Understanding their approach to machine learning robustness and trustworthiness will help you engage in meaningful conversations during interviews.
✨Tip Number 2
Network with current or former employees of Google DeepMind, especially those in research roles. They can provide insights into the company culture and expectations, which can be invaluable when preparing for your application.
✨Tip Number 3
Showcase your collaborative skills by discussing past experiences where you worked with cross-functional teams. Highlighting your ability to communicate complex ideas clearly will resonate well with the team-oriented environment at Google DeepMind.
✨Tip Number 4
Stay updated on the latest advancements in machine learning, particularly in areas like adversarial robustness and synthetic media. Being knowledgeable about current trends will demonstrate your passion and commitment to the field during discussions.
We think you need these skills to ace Research Engineer, Provenance
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in machine learning, programming, and any quantitative skills. Emphasise your Ph.D. or equivalent practical experience, and include specific projects that demonstrate your expertise in robust and trustworthy machine learning.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and the mission of Google DeepMind. Discuss how your background aligns with the role's responsibilities and how you can contribute to the team's goals. Be sure to mention any experience with GenAI models or adversarial robustness.
Showcase Your Research Impact: If you have published research or contributed to significant projects, summarise these in your application. Highlight the impact of your work and how it relates to the challenges mentioned in the job description, such as machine learning robustness and data trustworthiness.
Prepare for Technical Questions: Anticipate technical questions related to machine learning and computational techniques during the interview process. Brush up on your knowledge of scripting languages and pipelining tools, and be ready to discuss your approach to solving complex problems in this field.
How to prepare for a job interview at Google DeepMind
✨Showcase Your Machine Learning Expertise
Be prepared to discuss your experience with machine learning techniques in detail. Highlight specific projects where you've applied these skills, especially those related to robustness and trustworthiness, as this aligns closely with the role.
✨Demonstrate Collaborative Spirit
Since the role involves working with a team of researchers and engineers, emphasise your ability to collaborate effectively. Share examples of past teamwork experiences and how you contributed to achieving common goals.
✨Prepare for Technical Questions
Expect technical questions that assess your quantitative skills in maths and statistics, as well as your programming experience. Brush up on relevant concepts and be ready to solve problems on the spot.
✨Communicate Clearly and Effectively
You'll need to report and present research findings clearly. Practice summarising complex ideas succinctly and think about how you would explain your work to both technical and non-technical audiences.
