Apply to the vacancy...
Unfortunately, something went wrong while opening the page. Please try again.

Loading window...

Apply to the vacancy...
Unfortunately, something went wrong while opening the page. Please try again.

Loading window...

Sign up for Jobbird
An error occurred while opening the sign-up page. Please try again.

Loading window...

Forgot my password
Unfortunately, something went wrong while opening the page. Please try again.

Loading window...

Log out
Unfortunately, something went wrong while signing out. Please try again.

Loading window...

Job application sent
Something went wrong while logging in. Please try again.
Something went wrong while signing up. Please try again.

Loading window...

logo
  • 5 km
  • 10 km
  • 30 km
  • 50 km

  • All
  • 5 km
  • 10 km
  • 30 km
  • 50 km

  • All
Filters
Filters
Location and distance
  • 5 km
  • 10 km
  • 30 km
  • 50 km

  • All
Jobs posted from
Salary from (per month)
Filters
How our sorting works

The order in which job vacancies are displayed is determined by a composite score based on the following factors:

  • Keyword Relevance: How well your search terms match the vacancy details. We prioritize matches found in the job title, followed by job requirements, location names, and educational levels. Matches within general employer information or the organization's name carry a lower weight.
  • Commercial Prioritization (Premium Jobs): Vacancies paid for by employers ('Premium' or 'Sponsored') receive a ranking boost and will appear higher in the search results.
  • Recency (Date Relevance): Newer vacancies are prioritized. The relevance score of a vacancy is reduced by half once the posting is older than 30 days.
  • Proximity (Distance Relevance): Vacancies located closer to your search location are ranked higher. For vacancies located more than 30 km from the search center, the relevance score is halved.
The final ranking is established by multiplying all these individual factors to calculate the total relevance score.

K

R&D in AI Accelerator Optimization

KRAI Cambridge
new


Show Recently closed jobs

    K

    R&D in AI Accelerator Optimization

    KRAI Cambridge
    new
    Status Open
    Apply now

    Apply on the employer's website


    What we ask

    Education

    No minimum education required

    Job description

    About Us

    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 the non-profit MLCommons consortium, actively contributing to community research and open-source efforts for AI Systems.


    We are looking for exceptional R&D engineers to advance the state-of-the-art in AI accelerator programming (accelerating acceleration). The core challenge? Mapping rapidly evolving AI workloads onto rapidly evolving AI accelerator hardware (next generation accelerators, as well as traditional GPUs), 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 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 PhD) in Computer Engineering, Computer Science, or Natural Sciences.
    • 3+ years of hands-on experience optimizing compute-intensive workloads on accelerator hardware (GPUs, TPUs, NPUs, etc).
    • Experience with full-stack AI inference optimization: from models to runtimes to kernels.
    • Strong command of performance engineering tools: compilers, debuggers, profilers, simulators, and roofline analysis.
    • Workflow automation and reproducibility as first-class concerns.
    • Strong communication and collaboration skills.


    What We're NOT Looking For

    • We do NOT design AI hardware: we optimize software that runs on our customers' hardware.
    • We do NOT design AI pipelines: we get down to the nitty-gritty of AI inference.


    Why KRAI

    • Always at the bleeding edge: working with the SOTA 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.

    About the employer

    KRAI
    Apply now

    Apply on the employer's website

    Apply now

    Apply on the employer's website


    Vacancy actions

    Save as favorite
    Share vacancy
    Or apply later


    Cambridge England

    Jobs

    • Search for jobs
    • Jobs per location
    • Jobs per job profession
    • Jobs per employment
    • Jobs per educational attainment

    Jobbird

    • Switch to different region
    • Terms and Conditions
    © 2026 Jobbird