At a Glance
- Tasks: Lead innovative AI projects and shape the future of technology with Google Cloud.
- Company: Join Google, a leader in tech innovation and AI solutions.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with global influence and career advancement opportunities.
- Why this job: Make a real impact in AI while working with cutting-edge technologies.
- Qualifications: 8 years in software development and experience with machine learning and AI applications.
The predicted salary is between 80000 - 100000 € per year.
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience with machine learning design and infrastructure, including experience architecting Generative AI applications and agentic systems.
- 3 years of experience leading technical projects and providing technical leadership to cross-functional teams.
- Experience in Python and with production-level systems.
Preferred qualifications:
- Master's degree in Engineering, Computer Science, or related technical fields.
- 8 years of experience with data structures and algorithms.
- Experience architecting and developing software or infrastructure for scalable, distributed systems and with machine learning technologies.
- Experience building scalable software architectures that use Agentic or GenAI driven capabilities.
- Experience contributing to the developer community through open-source contributions, technical publications, or speaking at industry conferences in the field of AI/ML.
- Understanding of responsible AI practice.
About the job:
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
The Google Cloud Platform Generative AI Black Belt team helps customers unlock their potential with AI. As part of an entrepreneurial team in this rapidly growing business, you will help shape the future of businesses of all sizes using AI and ML.
The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world. We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
Responsibilities:
- Work with the team to identify and qualify business opportunities, understand key customer technical objections, and develop the strategy to resolve technical blockers.
- Provide AI expertise to support the technical relationship with Google’s customers, manage product and solution briefings, create demos, proof-of-concept work, and partner directly with product management to prioritize solutions impacting customer adoption to Google Cloud.
- Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to implement a complete solution Google Cloud.
- Support developers, creators, and enterprises to leverage Google’s Generative Language APIs so they can build their own AI products in the future.
- Travel to customer sites, conferences, and other related events as needed.
Staff Software Engineer, Google Cloud Generative AI Blackbelt in London employer: Google
At Google, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our Staff Software Engineers in the Google Cloud Generative AI Blackbelt team are not only at the forefront of cutting-edge technology but also benefit from extensive opportunities for professional growth and development. With a commitment to responsible AI practices and a supportive environment that encourages creativity, our employees can thrive while making a significant impact on businesses worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Software Engineer, Google Cloud Generative AI Blackbelt in London
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, conferences, or even online webinars. The more you engage with others, the better your chances of landing that dream job at Google.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your projects, especially those involving Generative AI or machine learning. This will give potential employers a taste of what you can bring to the table.
✨Ace the Interview
Prepare for technical interviews by brushing up on data structures, algorithms, and system design. Practice coding challenges and mock interviews to build confidence. Remember, Google loves problem solvers!
✨Apply Through Us
Make sure to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always looking for talented individuals who are passionate about AI and software development.
We think you need these skills to ace Staff Software Engineer, Google Cloud Generative AI Blackbelt in London
Some tips for your application 🫡
Show Off Your Experience:Make sure to highlight your 8 years of software development experience and any specific projects you've led. We want to see how your background aligns with the role, especially in machine learning and Generative AI applications.
Tailor Your Application:Don’t just send a generic application! Customise your CV and cover letter to reflect the skills and experiences mentioned in the job description. We love seeing how you can bring fresh ideas to our team.
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language and avoid jargon unless it's relevant. We appreciate a well-structured application that gets straight to the point!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Google
✨Know Your Stuff
Make sure you brush up on your technical skills, especially in Python and machine learning. Be ready to discuss your experience with generative AI applications and scalable systems. Prepare to explain complex concepts in a way that shows your depth of understanding.
✨Showcase Leadership Experience
Since the role requires leading technical projects, think of specific examples where you've taken charge. Highlight how you guided cross-functional teams and overcame challenges. This will demonstrate your ability to lead and inspire others.
✨Prepare for Problem-Solving Questions
Expect to tackle some tricky problem-solving scenarios during the interview. Practice coding challenges and algorithm questions that reflect real-world applications. This will help you showcase your analytical skills and approach to tackling complex issues.
✨Engage with the Community
If you've contributed to open-source projects or spoken at conferences, be sure to mention these experiences. It shows your passion for the field and commitment to responsible AI practices. Plus, it can set you apart from other candidates!
