Hardware‑Aware AI Research Engineer in Cambridge

Hardware‑Aware AI Research Engineer in Cambridge

Cambridge Full-Time 60000 - 80000 £ / year (est.) No working from home possible
EngineersOfAI

At a Glance

  • Tasks: Advance AI research with hardware-aware algorithms and scalable implementations.
  • Company: Join Graphcore, a leader in AI hardware innovation.
  • Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
  • Other info: Dynamic team environment with exciting challenges and career advancement.
  • Why this job: Make a real impact in AI by collaborating on cutting-edge projects.
  • Qualifications: Strong software engineering skills and experience in lower-level programming.

The predicted salary is between 60000 - 80000 £ per year.

Graphcore is seeking a Research Engineer to advance AI research with hardware-aware algorithms and scalable implementations.

You will work with researchers and engineers on a range of topics from efficient training and inference to world models and reinforcement learning.

The role emphasizes strong software engineering, lower-level programming for hardware efficiency, and collaboration across teams to deliver impactful AI hardware developments.

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Hardware‑Aware AI Research Engineer in Cambridge employer: EngineersOfAI

Graphcore is an exceptional employer, offering a dynamic work environment where innovation thrives and every team member can contribute to groundbreaking advancements in AI technology. With a strong focus on employee growth, Graphcore provides ample opportunities for professional development and collaboration with industry experts, all while being part of the prestigious SoftBank Group. Located in a vibrant tech hub, employees enjoy a culture that values creativity, inclusivity, and the chance to make a significant impact in the rapidly evolving field of artificial intelligence.

EngineersOfAI

Contact Details:

EngineersOfAI Recruitment Team

We think you need these skills to ace Hardware‑Aware AI Research Engineer in Cambridge

AI Research
Hardware-Aware Algorithms
Scalable Implementations
Efficient Training
Inference Techniques
World Models
Reinforcement Learning