Staff Software Engineer, Performance and Kernel, DeepMind
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products.
- 5 years of experience in power or performance modeling or system performance analysis.
- 5 years of experience with Linux Kernel development and software and hardware architecture.
- 3 years of experience with software design and architecture.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- Deep expertise in at least some of the following: operating systems, networking systems, storage systems, analytics, machine learning, working with distributed query processing and deep functional flows.
About the job
At DeepMind our mission is to build the world's first general-purpose learning agent. Central to this mission is the complex task of measuring the intelligence of our prototypes. As a Software Engineer, you will be working with the cutting edge AI agents developed by our exceptional team of Machine Learning and Neuroscience research scientists. Your responsibilities will include everything from creating systems for agent testing using 2D and 3D games to developing test problems within physics simulators. You will create graphical visualization of results, build competitive agent leaderboards and test new algorithms on robots. To succeed in this role you will need to have a strong foundation in software engineering and enjoy working on a wide range of challenging problems within a mission-driven team.
Accelerators have become a strategic differentiator in today’s hyperscale AI competition. Unlike classic data center infrastructure, these new codesigned systems must meet future demands as our workloads continue to evolve and mutate. Through our projects, we are deploying new hardware in Google data centers to drive enhanced capabilities and efficiency, partnering closely with the teams responsible for Google’s technical infrastructure to successfully deliver these systems.
We are a co-design team within DeepMind’s GenAI Systems, operating across Google’s vertically integrated stack. Our expertise spans hardware including architecture, logic design, design verification, and physical design software, such as compilation, performance optimization, libraries, operating systems, and kernels, and algorithms, covering ML model design, optimization methods, numerics, and sparsity. In these fields, we conduct research while delivering production-quality hardware and software products.
Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Write low-level performance software for a new systolic array accelerators.
- Identify high-value algorithms and problems that are a match to this new machines.
- Use that direct experience delivering production code to build programming infrastructure to ease programming on the new accelerator for the performance software engineers and general software engineers who follow.
- Collaborate with application, algorithm, and performance-tuning experts to codesign solutions for the best efficiency, performance, and programmability.
- Communicate the performance, programmability, and efficiency results to our team and to our partner teams.
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