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AI role · Open offer

Junior ML Engineer — GenAI delivery

Faculty

Full-time
Junior
Applied AI
Hybrid
160 Old Street, London, England EC1V 9BW, United Kingdom · Hybrid
London, United Kingdom
£45k–£60k

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.

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At a glance

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

Employment: Full-time
Workplace: Hybrid
Location: 160 Old Street, London, England EC1V 9BW, United Kingdom · Hybrid
Compensation: £45k–£60k
Experience level: Junior
Team: Applied AI
Benefits & perks: Mentorship, training budget.
How to apply: Coursework or internship project with metrics.
Company site: faculty.ai
Listed: Jul 11, 2026
Updated: Aug 3, 2026

About this role

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

Faculty is hiring a Junior Junior ML Engineer — GenAI delivery on the Applied AI 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.

Faculty AI delivery teams onboard early-career ML engineers onto client GenAI and forecasting projects.

Junior ML Engineer (London): mentorship, feature engineering, eval notebooks, and guarded production contributions.

What you will do

Deliver production-grade applied ML with mentorship with measurable quality, latency, and cost targets.
Build offline evals and online monitoring before scaling to full traffic.
Collaborate with product, design, legal, or domain experts on safe rollout.
Write clear RFCs, runbooks, and postmortems for cross-team learning.

What we look for

Multiple shipped ML/LLM features—not coursework-only portfolios.
Strong Python, SQL, and experimentation discipline.
Clear communication for remote or hybrid stakeholders.
Work authorization for the listed country.

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.

Tools & stack

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

JupyterTool
Regular use of Jupyter in the LLM & generative AI stack—configuration, debugging, and team conventions.

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: Coursework or internship project with metrics.
Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, SQL, and Jupyter.
You are early-career but can point to one end-to-end project (course, internship, or OSS) with honest metrics and what you would improve next.
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: £45k–£60k, benefits in At a glance) and your expectations align.

Apply

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What the employer asked for

Coursework or internship project with metrics.

Sign in with a candidate account to apply

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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