At a Glance
- Tasks: Develop and optimise cutting-edge AI workloads on next-gen hardware.
- Company: Join KRAI, a leader in AI infrastructure optimisation.
- Benefits: Work with the latest tech and make a real-world impact.
- Other info: Join a small, friendly team with excellent career growth opportunities.
- Why this job: Be at the forefront of AI innovation and contribute to open-source projects.
- Qualifications: Advanced degree in relevant fields and experience with performance engineering tools.
The predicted salary is between 70000 - 90000 £ per year.
KRAI is a cutting-edge AI infrastructure optimization company, a proven and valuable strategic partner for top accelerator designers, server manufacturers, and cloud providers.
We are a Founding Member of MLCommons, actively contributing to community research and open-source efforts for AI Systems.
We are looking for R&D engineers to advance the state-of-the-art in AI accelerator programming.
The core challenge?
Mapping rapidly evolving AI workloads onto rapidly evolving AI hardware (GPUs and next-generation accelerators), while navigating an infinite space of performance, quality, and cost trade-offs.
Our approach combines rigorous performance engineering with systematic agentic techniques.
We aim for results that genuinely surprise even seasoned professionals.
- What You’ll Do
- Developing and optimizing low-level compute kernels for the latest AI workloads.
- Working across a range of accelerator architectures, including hardware that is years from public release.
- Exploring performance, efficiency, and quality trade-offs.
- Driving full-stack inference optimization: from AI models all the way down to hardware.
- Applying both traditional performance engineering tools (compilers, profilers, roofline models, simulators) and frontier AI techniques to solve complex optimization problems.
- Collaborating with top accelerator designers, server manufacturers and cloud providers to deliver best-in-class performance results.
- What We’re Looking For
- Advanced degree (MSc or Ph D) in Computer Engineering, Computer Science, or Natural Sciences.
- 3+ years of hands-on experience optimizing compute-intensive workloads on accelerator hardware (GPU, FPGA, or similar).
- Strong command of performance engineering tools: compilers, debuggers, profilers, simulators, and roofline analysis.
- Experience with full-stack AI inference optimization: from models to runtimes to kernels.
- Strong communication and collaboration skills.
- Why KRAI
- Always at the bleeding edge: working with the latest AI models and pre-release accelerator hardware.
- Real-world impact: directly influencing hardware roadmaps and procurement decisions at major technology companies.
- Active contributions to open-source and research: getting high visibility and recognition in the AI Systems community.
- Small well-knit team with deep technical expertise and friendly culture.
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