At a Glance
- Tasks: Write code for the TPU compiler and optimise machine learning models.
- Company: Join Google, a leader in tech innovation and digital transformation.
- Benefits: Competitive salary, inclusive culture, and opportunities for growth.
- Other info: Dynamic environment with diverse projects and career advancement opportunities.
- Why this job: Make an impact on cutting-edge AI technologies and work with brilliant minds.
- Qualifications: PhD enrolment or graduation, coding experience, and passion for AI.
The predicted salary is between 28800 - 48000 € per year.
Minimum qualifications:
- Experience with coding in data structures, algorithms and software design.
- Research experience in Artificial Intelligence, Distributed Systems, Machine Learning, Data Mining, Natural Language Processing, Image Classification, Spam Fighting, or related fields.
- Work or educational experience in Machine Learning or Artificial Intelligence.
Preferred qualifications:
- Currently enrolled in or graduated from a PhD program.
- Experience working with parallel computing.
- Experience with compilers and compiler construction.
- Excellent debugging and programming concurrent/parallel computations, and working on accelerators such as VLIW, Vector machines, GPUs, or DSPs.
Responsibilities:
- Write product or system development code for the TPU compiler (in C++).
- Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
- Contribute to a compiler which scales-out machine learning models across accelerators like TPU/Graphics Processing Unit (GPU) at Google and Cloud.
- Design and implement performance optimizations and critical features, which increase the velocity of important production teams.
- Apply AI to the development of the Compiler and to the Compiler itself.
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.
Software Engineer, TPU Compiler, PhD, Early Careers in London employer: WeAreTechWomen
At Google, we pride ourselves on fostering a dynamic and inclusive work culture that encourages innovation and collaboration. As a Software Engineer in the TPU Compiler team, you will have access to cutting-edge technology and the opportunity to work on impactful projects that shape the future of machine learning. With a strong emphasis on employee growth, mentorship, and the chance to switch teams, Google offers a unique environment where your contributions are valued and your career can flourish.
StudySmarter Expert Advice🤫
We think this is how you could land Software Engineer, TPU Compiler, PhD, Early Careers in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work at Google or similar companies. Use platforms like LinkedIn to connect and engage with them; you never know who might help you land that interview.
✨Tip Number 2
Prepare for technical interviews by practicing coding problems related to data structures and algorithms. Websites like LeetCode or HackerRank can be super helpful. Remember, the more you practice, the more confident you'll feel when it’s time to shine!
✨Tip Number 3
Show off your projects! If you've worked on any relevant projects, make sure to highlight them during interviews. Discuss the challenges you faced and how you overcame them, especially if they relate to machine learning or compilers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search. So go ahead, hit that apply button!
We think you need these skills to ace Software Engineer, TPU Compiler, PhD, Early Careers in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your coding experience, especially in data structures and algorithms. We want to see how you've tackled problems in your past projects, so don’t hold back on showcasing your best work!
Tailor Your Application:Take a moment to customise your application for the Software Engineer role. Mention any relevant research or projects related to AI, machine learning, or compilers. This helps us see how you fit into our team and the exciting work we do.
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language and avoid jargon unless it's necessary. We appreciate a well-structured application that gets straight to the point!
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’s super easy to do!
How to prepare for a job interview at WeAreTechWomen
✨Know Your Tech Inside Out
Make sure you brush up on your coding skills, especially in C++. Be ready to discuss data structures, algorithms, and software design principles. Practising coding challenges related to parallel computing and compiler construction can really help you stand out.
✨Showcase Your Research Experience
Since the role involves AI and machine learning, be prepared to talk about your research projects. Highlight any experience you have with distributed systems or natural language processing. Use specific examples to demonstrate how your work aligns with the responsibilities of the TPU team.
✨Prepare for Design Reviews
Familiarise yourself with the design review process. Think about how you would approach a design problem and be ready to discuss your thought process. This shows that you can collaborate effectively with peers and stakeholders, which is crucial for this role.
✨Be Ready to Discuss Optimisations
The job requires implementing performance optimisations, so come prepared with ideas. Think about past experiences where you improved system performance or efficiency. Being able to articulate these experiences will demonstrate your ability to contribute to critical features for the TPU compiler.
