At a Glance
- Tasks: Prototype and deliver scalable engineering solutions for AI safety and performance.
- Company: Join Google DeepMind, a pioneering AI lab focused on transformative technology.
- Benefits: Diverse learning opportunities, competitive salary, and commitment to ethics in AI.
- Other info: Collaborate with top researchers and contribute to the wider AI community.
- Why this job: Make a real impact on global challenges through innovative AI research.
- Qualifications: Bachelor's degree in a technical field and extensive experience in machine learning.
The predicted salary is between 80000 - 100000 € per year.
Minimum qualifications:
- Bachelor's degree in Computer Science, Machine Learning, Mathematics, or a related technical field, or equivalent practical experience.
- 8 years of experience in machine learning engineering or large-scale software systems.
- 3 years of experience in Python programming.
- 3 years of experience with ML frameworks such as JAX, PyTorch, or TensorFlow.
Preferred qualifications:
- Master's degree or PhD in Computer Science, Engineering, or a related field with a focus on Machine Learning.
- Experience working directly on AI safety, adversarial robustness, jailbreak evaluation, or responsible AI research.
- Experience in Python and C++ for high-performance ML library development.
- Experience with adversarial machine learning, red-teaming, AI safety evaluation, or security research.
- Experience building evaluation frameworks, benchmarks, or automated testing pipelines for ML models.
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. 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 DeepMind, 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:
- Prototype and deliver scalable engineering solutions rapidly.
- Architect and optimize training and inference pipelines to evaluate the frontier language models.
- Develop post-training strategies to mitigate adversarial risks including jailbreak and prompt injection attacks.
- Collaborate with Research Scientists to translate safety research into implementations and present results to cross-functional stakeholders.
- Build and maintain evaluation infrastructure to systematically track model safety performance.
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.
Research Engineer, Responsibility Engineering, DeepMind in London employer: Google DeepMind
At Google DeepMind, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. Our research engineers are empowered to tackle real-world challenges in AI while benefiting from diverse learning opportunities and career pathways. With a commitment to ethical practices and public benefit, our teams work in a dynamic environment that values contributions to the wider research community, making it a truly rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Research Engineer, Responsibility Engineering, DeepMind in London
✨Tip Number 1
Network like a pro! Reach out to folks in your field on LinkedIn or at industry events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and ML frameworks like JAX or PyTorch. This gives you a chance to demonstrate your expertise beyond just words.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and scenarios related to AI safety and adversarial robustness. Practising with a friend can help you feel more confident when it’s your turn to shine.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Research Engineer, Responsibility Engineering, DeepMind in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your experience in machine learning and Python programming. We want to see how your background aligns with the qualifications listed, so don’t hold back on showcasing your projects and achievements!
Tailor Your Application:Take a moment to customise your application for this role. Use keywords from the job description to demonstrate that you understand what we’re looking for. This helps us see how you fit into our team at StudySmarter.
Be Clear and Concise:When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon unless it’s necessary. Make your points easy to read and digest – we’re keen to get to know you without wading through fluff!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved.
How to prepare for a job interview at Google DeepMind
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python and the ML frameworks mentioned, like JAX, PyTorch, or TensorFlow. Brush up on your coding skills and be ready to demonstrate your knowledge through practical examples or even live coding during the interview.
✨Showcase Your Experience
With 8 years of experience in machine learning engineering, you’ll want to highlight specific projects where you’ve tackled real-world problems. Be prepared to discuss your role in these projects, especially any work related to AI safety or adversarial robustness.
✨Prepare for Technical Questions
Expect deep technical questions that assess your understanding of machine learning concepts and practices. Review common algorithms, evaluation metrics, and be ready to explain how you would approach building evaluation frameworks or testing pipelines.
✨Demonstrate Collaboration Skills
Since the role involves working closely with Research Scientists and cross-functional teams, be ready to share examples of how you’ve successfully collaborated in the past. Highlight your communication skills and how you’ve translated complex research into actionable implementations.
