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Signal AI careers — NLP Engineer | London · Ganloss

AI role · Open offer

Senior NLP Engineer — media intelligence

Signal AI

Full-time
Senior
NLP platform
Hybrid
1 Finsbury Avenue, London, England EC2M 2PP, United Kingdom · Hybrid
London, United Kingdom
£90k–£120k + equity

This listing is optimized for AI-native talent: clear skills and tools so candidates know if they fit before they apply—and so you spend less time screening mismatches.

4 skills1 tool

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At a glance

How you'll work, where, and key listing dates.

Employment: Full-time
Workplace: Hybrid
Location: 1 Finsbury Avenue, London, England EC2M 2PP, United Kingdom · Hybrid
Compensation: £90k–£120k + equity
Experience level: Senior
Team: NLP platform
Benefits & perks: Equity, pension, hybrid 3/2.
How to apply: Entity extraction or topic classification at news scale.
Company site: www.signal-ai.com
Listed: Jun 5, 2026
Updated: Aug 3, 2026

About this role

What the team is looking for and how this position fits.

Signal AI is hiring a Senior Senior NLP Engineer — media intelligence on the NLP platform team (Hybrid · London, United Kingdom). This is a hands-on role in LLM & generative AI—not a generic “AI enthusiast” post.

You will own LLM features, retrieval, agents, and evaluation end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.

Signal AI monitors global news and regulatory sources for enterprise comms and risk teams.

Senior NLP Engineer: entity linking, event detection, and LLM-assisted summarisation across 100+ languages.

Hybrid London — work with domain experts to keep models aligned with geopolitical and ESG narratives.

What you will do

Train and deploy classifiers for topics, entities, and sentiment at news scale.
Integrate LLM summarisation with human editorial QA workflows.
Improve data labelling efficiency with active learning loops.
Maintain SLAs for near-real-time ingestion pipelines.

Stack & environment

Python, PyTorch, Spark, SQL warehouses.
Hybrid Finsbury Avenue office.

What we look for

NLP at scale (millions of documents/day).
Experience with multilingual or low-resource language challenges.
Clear communication for PM and analyst stakeholders.

Skills we're hiring for

What each capability means for this role—not a keyword checklist.

Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
PyTorch
Training and inference with PyTorch: reproducible experiments, checkpointing, and deployment-minded exports.
SQL
Analytical SQL for features, cohorts, label quality, and experiment analysis at scale.
NLP
Text pipelines: tokenization, fine-tuning, evaluation, and guardrails for user-facing language features.

Tools & stack

Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).

SparkTool
Distributed feature generation and batch scoring on large tabular or event datasets.

You're a strong fit if…

Tailored to this listing—use it as a self-check before you apply.

You can show evidence in your application: Entity extraction or topic classification at news scale.
Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, SQL, NLP, and Spark.
You have owned LLM features, retrieval, agents, and evaluation in production: debugging live issues, running postmortems, and iterating from real user or business signals.
You are comfortable with the hybrid rhythm (Hybrid · London, United Kingdom)—onsite collaboration when it matters, deep work when remote.
You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.
You read the full listing (comp: £90k–£120k + equity, benefits in At a glance) and your expectations align.

Apply

Candidate accounts only: add your headline and bio on My account, and optionally a CV link or PDF so recruiters see your full résumé. Then write a short pitch below—applications use your login email.

What the employer asked for

Entity extraction or topic classification at news scale.

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Register, add a headline and bio, then you can attach a CV link or PDF on My account before you apply. That keeps applications tied to your profile and makes it easier for employers to review your background.

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