Staff Research Engineer: Agentic Evaluation & Benchmarks

Callosum Technologies Ltd.

Greater London

Hybrid

GBP 90,000 - 140,000

Full time

14 days+

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Benefits offered by this job

Competitive salary
Equity & Ownership
Private healthcare
Visa sponsorship & relocation
London office in-person work

Job summary

Callosum Technologies Ltd. is building the next generation of AI systems through application-aware orchestration across heterogeneous models and hardware.

This role focuses on agentic evaluation, establishing robust benchmarks and evidence-based measures to locate failures and improve designs. You will design and run experiments, quantify uncertainty, and publish results to guide the company’s future products.

Qualifications

  • Evidence that you can run research of your own and design experiments.
  • Hands-on experience with LLMs in agentic settings and multi-step tasks.
  • Strong statistical discipline and uncertainty quantification.
  • Strong software engineering skills and ability to contribute to a large codebase.
  • Excellent communication to translate research into actionable guidance.

Responsibilities

  • Design benchmarks and evaluation suites for agentic behaviour across multi-turn tasks.
  • Develop methodological tooling: power analysis, variance across runs, validity checks.
  • Act as independent voice on result quality; perform red-teaming of evaluations.
  • Convert raw traces into structured evidence and failure taxonomies.
  • Predict system capabilities from partial evidence and framework tasks.

Skills

Research capability
LLMs in agentic settings
Statistics
Engineering
Communication
Benchmarks
Empirical methods
Automated grading
Publications

Job description

Callosum Technologies Ltd. is building the next generation of AI systems through application-aware orchestration across heterogeneous models and hardware.

This role focuses on agentic evaluation, establishing robust benchmarks and evidence-based measures to locate failures and improve designs. You will design and run experiments, quantify uncertainty, and publish results to guide the company’s future products.

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