At a Glance
- Tasks: Prototype scalable engineering solutions and optimise AI safety strategies.
- Company: Join Google DeepMind, a pioneering AI lab focused on transformative technology.
- Benefits: Competitive salary, diverse learning opportunities, and a focus on ethics in AI.
- Other info: Dynamic environment with varied career pathways and a commitment to public benefit.
- Why this job: Make a real impact in AI development while collaborating with top researchers.
- 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.
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.
Research Engineer, Responsibility Engineering, DeepMind in London employer: Google
At Google DeepMind, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. Our commitment to employee growth is evident through diverse learning opportunities and the chance to work on groundbreaking AI projects that have a meaningful impact on society. Located in a vibrant tech hub, we offer a dynamic work environment where your contributions are valued, and you can engage with leading experts in the field while advancing your career in a supportive atmosphere.
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 the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and AI safety. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on technical questions and real-world problem-solving scenarios. Practice coding challenges and be ready to discuss your past experiences in detail, especially those that align with the role.
✨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:Customise your CV and cover letter to reflect the specific responsibilities and qualifications mentioned in the job description. We love seeing candidates who take the time to connect their experiences directly to what we’re looking for.
Be Clear and Concise:When writing your application, keep it straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s relevant to the role. Make it easy for us to see why you’d be a great fit!
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 ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Google
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning frameworks like JAX, PyTorch, and TensorFlow. Be ready to discuss your experience with Python programming and how you've applied it in real-world scenarios. The more specific examples you can provide, the better!
✨Showcase Your Projects
Prepare to talk about any relevant projects you've worked on, especially those involving AI safety or adversarial robustness. Highlight your role in these projects and the impact they had. This will demonstrate your hands-on experience and understanding of the field.
✨Understand the Company’s Mission
Familiarise yourself with DeepMind's focus on responsible AI research and public benefit. Be ready to discuss how your values align with theirs and how you can contribute to their mission of solving complex global challenges through AI.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the role and the company. Inquire about their current projects, challenges they face in AI safety, or how they measure success in their engineering solutions. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
