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AI role · Open offer

ML Engineer — document AI & LLM

Pennylane

Permanent (CDI)
Full-time
Senior
AI
Hybrid
10 Rue de Penthièvre, Paris, IDF 75008, France · Hybrid
Paris, France
EUR 75k-100k/year + BSPCE

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: Permanent (CDI), Full-time
Workplace: Hybrid
Location: 10 Rue de Penthièvre, Paris, IDF 75008, France · Hybrid
Compensation: EUR 75k-100k/year + BSPCE
Experience level: Senior
Team: AI
Benefits & perks: BSPCE, mutuelle, produit compta moderne.
How to apply: OCR + LLM sur documents financiers avec QA.
Company site: www.pennylane.com
Listed: Jul 2, 2026
Updated: Aug 3, 2026

About this role

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

Pennylane is hiring a Senior ML Engineer — document AI & LLM on the AI team (Hybrid · Paris, France). 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.

Pennylane combine comptabilité et logiciel pour les entreprises françaises. L'IA automatise saisie, rapprochement et insights.

ML Engineer (Paris) : OCR + LLM sur documents comptables, avec contrôles qualité et audit trail.

What you will do

Ship production document AI for accounting with clear evaluation, monitoring, and rollback paths—not demo-only notebooks.
Partner with product, design, and domain experts on requirements, trade-offs, and safe rollout.
Improve data quality, labeling, and offline metrics that correlate with business KPIs.
Document architectures and runbooks for on-call and customer-facing teams.
Mentor engineers on testing, observability, and responsible AI practices.

What we look for

Strong Python and modern ML/LLM stack experience with multiple shipped features.
Comfort with SQL, experimentation, and communicating results to non-technical stakeholders.
Pragmatic ownership from prototype to production—including cost and latency budgets.
Eligible to work in the listed country; professional English (French a plus for Paris roles).

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.
LangChain
Orchestrating LLM chains, tools, and retrieval with observable steps and failure handling.
Computer Vision
Image or video models with clear eval harnesses (precision/recall, calibration, or domain-specific scores).

Tools & stack

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

Vector DBsTool
Embedding storage, hybrid search, and freshness strategies for RAG and semantic retrieval.

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: OCR + LLM sur documents financiers avec QA.
Several of these show up in recent shipped work—not only on your CV: Python, LangChain, Computer Vision, and Vector DBs.
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 · Paris, France)—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: EUR 75k-100k/year + BSPCE, benefits in At a glance) and your expectations align.

Apply

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What the employer asked for

OCR + LLM sur documents financiers avec QA.

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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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