At a Glance
- Tasks: Write and optimise code for cutting-edge machine learning technologies.
- Company: Join Google, a leader in tech innovation and collaboration.
- Benefits: Competitive salary, health benefits, and opportunities for remote work.
- Why this job: Make a massive impact on the future of machine learning and technology.
- Qualifications: Experience in C++, data structures, and algorithms; passion for problem-solving.
- Other info: Dynamic team environment with endless growth and learning opportunities.
The predicted salary is between 36000 - 60000 £ per year.
- Bachelor’s degree or equivalent practical experience.
- 1 year of experience with data structures or algorithms.
- Experience with C++, compiler construction and performance optimization.
Preferred qualifications:
- Master\’s degree in Computer Science or a related technical field.
- Experience with Machine Learning architecture and infrastructure.
- Understanding of accelerators, for example, VLIW, Vector machines, GPUs or DSPs.
- Understanding of debugging correctness and performance issues at all levels of the stack.
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 TPU Backend and NPI team is at the crux of Machine learning, Compilers and TPU hardware. We collaborate with teams across hardware and software, and enable Google to have the industry\’s most performant machine learning chip (TPU) at the hands of machine learning (ML) modeling teams. The vast majority of all machine learning at Google flows through tools that the TPU backend and NPI team is creating, so impact is both immediate and massive. Enable a novel processor to accelerate machine learning workloads. This hardware will be deployed at scale and will power some of Google\’s most critical production workloads. Opportunities include performance optimization, programmability, usability and co-design of next generation hardware.
Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google\’s product portfolio possible. We\’re proud to be our engineers\’ engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.
Responsibilities
- Write product or system development code. Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
- Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
- Contribute to the TPU compiler for a novel processor designed to accelerate machine learning workloads. Target and compile high-performance implementations of operations at a distributed scale.
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google\’s EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
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Software Engineer II, TPU Compiler employer: Google Inc.
Contact Detail:
Google Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Engineer II, TPU Compiler
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Google, especially those in the TPU Compiler team. A friendly chat can give us insider info and might even lead to a referral!
✨Tip Number 2
Show off your skills! Prepare for technical interviews by practicing coding challenges and system design problems. Use platforms like LeetCode or HackerRank to sharpen your C++ and algorithm skills.
✨Tip Number 3
Be ready to discuss your projects! Whether it's compiler construction or machine learning, we want to hear about your hands-on experience. Make sure you can explain your thought process and the impact of your work.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're serious about joining the team. Don’t forget to tailor your application to highlight your relevant experience!
We think you need these skills to ace Software Engineer II, TPU Compiler
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with C++, data structures, and algorithms in your application. We want to see how you've tackled challenges in these areas, so don’t hold back!
Tailor Your Application: Take a moment to customise your application for the Software Engineer II role. Mention any relevant projects or experiences that align with our focus on machine learning and compiler construction.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so make sure your points are easy to understand and get straight to the heart of your qualifications.
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. We can’t wait to hear from you!
How to prepare for a job interview at Google Inc.
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of data structures, algorithms, and C++. Be ready to discuss your experience with compiler construction and performance optimisation, as these are key areas for the role. Practising coding problems related to these topics can really help you shine.
✨Showcase Your Problem-Solving Skills
Prepare to demonstrate how you've tackled complex issues in past projects. Think about specific examples where you debugged performance issues or optimised code. This will show your potential employer that you can handle the challenges they face in a fast-paced environment.
✨Understand Machine Learning Fundamentals
Since this role involves working with machine learning architecture, it’s crucial to have a solid grasp of ML concepts. Familiarise yourself with how TPUs work and be prepared to discuss their impact on performance. This knowledge will set you apart from other candidates.
✨Be Ready for Design Reviews
Expect to participate in design reviews during the interview process. Brush up on how to articulate your design choices and provide constructive feedback. Showing that you can collaborate effectively with peers and stakeholders will highlight your leadership qualities.