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Research engineer

Cambridge
Hiverge
Research engineer
Posted: 1 October
Offer description

Who we are

At Hiverge, our mission is to build algorithmic superintelligence: an AI discovery engine that automatically writes algorithms for the most critical optimisation problems.

Our founding team is composed of world-class researchers from Google DeepMind and University of Cambridge, having co-developed AlphaTensor, FunSearch, and Nobel-prize winning AlphaFold. At Hiverge, you will be working with the brightest minds in AI, algorithms, and mathematics.

If you’re passionate about AI and eager to shape transformative technologies, we’d love to hear from you.


About this role

This role designs, trains, and evaluates LLM‑centric systems. The work blends implementation, experimentation, and benchmarking.

As a Research Engineer you will:

* Build scalable experimentation foundations with strong reproducibility and observability.
* Create robust prompt and code-selection tooling.
* Make our system faster and more efficient through optimized inference and infrastructure.
* Work with the team (ML engineers and researchers) to implement new ideas.
* Engage with the research community to advance the state of algorithmic discovery.


Qualifications

* Masters degree in Computer Science, Engineering, related field, or equivalent experience.
* Strong coding skills in Python and experience with PyTorch/JAX and modern LLM tooling for inference and fine‑tuning.
* 3+ years in applied research engineering or equivalent, with shipped research systems or strong open‑source repositories in LLMs, search/RL, or compilers/verification.
* Exposure to evaluation frameworks, unit/property‑based testing, and performance profiling.


What sets the candidate apart

* Contributions to open research or community tooling.
* Familiarity with algorithm design, and practical understanding of reinforcement learning, evolutionary methods and optimization methods.

We offer competitive compensation, generous benefits packages, and offer a stimulating work environment, with the opportunity to contribute to the future of generative AI.

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