About the role
What will you do at Swiftkey?
Develop and tune the compute infrastructure stack allocating NVIDIA Grace Blackwell (GB) and Vera Rubin (VR) resources to AI workloads. Scale GPU clusters across hardware generations to thousands of accelerators and beyond. Use operational data and workload insights to inform the compute (GPU and CPU) roadmap for large-scale AI research.
Partner with model-development teams to improve the infrastructure used to train and serve AI models. Find practical ways around roadblocks and deliver improvements rapidly, iterating with users in a fast-paced, design-driven environment. A bachelor's degree in computer science or a related technical field and at least six years of engineering experience writing code in languages such as C, C++, Python, Go, or JavaScript; or equivalent practical experience.
Significant additional engineering experience, with a master's degree or equivalent practical experience, building production software and distributed systems. Experience with Ray, Kubernetes, Kueue, Volcano, or another AI-focused system for scheduling, scaling, or fault tolerance is especially relevant.
Which skills does this role require?
Make your next move
Build a shortlist and prepare
Identify the requirements you can demonstrate, then choose examples from your work to discuss with the hiring team.
- Build a focused shortlist before you applyCompare role requirements with your experience and give each application a clear reason.
- Platform engineering jobsCompare current openings and review what to look for in this role.
- Practice explaining your experience in an interviewRehearse your answers before meeting the hiring team.
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Role information can change. Prepin can help you prepare, but does not submit an application for this role.