- Location
- Singapore
- Department
- Engineering
- Seniority
- Senior
- Experience
- 5+ years
- Education
- PhD
- Closing date
- Today
Description
Senior Software Engineer, Cloud GPU
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Minimum qualifications:
- Bachelor’s degree in Computer Science or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
Preferred qualifications:
- Master's degree or PhD in Computer Science or a related technical field.
- 5 years of experience with data structures and algorithms.
- 1 year of experience in a technical leadership role, including a track record of coaching and mentoring junior engineers.
- Experience with large-scale Cloud Infrastructure, Cloud Services, or GPUs.
- Ability to communicate fluently in English and Mandarin to effectively support client management in the region.
About the job
The Cloud GPU team is central to Artificial Intelligence (AI) innovation, dedicated to building and maintaining an industry-leading Graphics Processing Unit (GPU) fleet and AI Platform. Our core mission is to empower Google Cloud's most sophisticated training and inference customers by providing unparalleled computational resources. We are responsible for the entire lifecycle of GPU offerings within Google Cloud, from the initial launch of new GPU families to ensuring their optimal reliability and operational excellence for AI workloads. The team works at the intersection of hardware, software, data science and applied AI, constantly pushing the boundaries of what's possible in accelerated computing. We collaborate closely with internal and external partners to deliver the foundational infrastructure that fuels advancements in artificial intelligence across industries.As a Senior Software Engineer, you will develop the next-generation technologies that change how users connect, explore, and interact with information and one another. You will bring ideas from all areas, including distributed computing, large-scale system design, networking and data storage, artificial intelligence, etc. You will focus on delivering tangible growth in the AI infrastructure space.
Responsibilities
- Design and implement highly scalable software solutions and Machine learning (ML) infrastructure, supporting the integration of new GPUs in Google Compute Engine and scaling the existing Cloud GPU fleet.
- Write, test, and review complex product code and technical specifications, collaborating with peers through design and code reviews to ensure best practices in software architecture, accuracy, testability, and efficiency.
- Maintain and support existing accelerator solutions by actively triaging, debugging, and resolving complex production issues, analyzing their root causes and impact on hardware, network, and service operations.
- Engage with customers to troubleshoot and resolve issues promptly, ensuring optimal reliability and operational excellence for AI workloads.
- Contribute to technical documentation and adapt educational content based on product updates, system developments, and user feedback to ensure seamless knowledge sharing across the team.
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