Description review

G-Research | London UK, on-site | Full-time

G-Research · Full-time · back to the listing

HR standards

50/100

needs work

Title ↔ description

35/100

poor

Reads as

Backend Engineer

98% confident

What this role officially is

software developer — ESCO, the EU occupation classification

Software developers implement or program all kinds of software systems based on specifications and designs by using programming languages, tools, and platforms.

Also known as: application developer, application programmer, solutions developer, programmer, software specialist, application software developer

How others title the same work

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What the listing never says

  • No section describes what the person would actually do. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
  • No location or timezone policy stated, so a candidate cannot tell where they may work from. Scope clarity

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

G-Research is a leading quant finance company. Big compute farm, interesting problems.
My team is hiring senior engineers to work on our (actually world class) DAG scheduling infra for distributing research and production workloads across the compute farm. What we do is roughly:
* maintain and improve the SDKs for that scheduler in Python, F#, and C#
* add interesting new features to the scheduler itself
* maintain and improve a web backend and UI for quants and engineers to monitor their jobs, increasingly with high availability requirements
* translate bidirectionally at the business level between low-level infra providers and quant/ML researchers
Some functional experience preferred, because our core product is in F#. Lots of dealing with very smart researchers and engineers, with the kind of fun problems arising when you run large ML workloads at scale.
[email protected] or my personal [email protected]

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 16 points (from 66 before penalties). Reviewed 21 Sep 2026.