AI role · Open offer

Lead Computer Vision Engineer

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Focus: Vision AI

Paris · 100-300 employees · Scale-up · GenAI: No

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: 42 Rue du Louvre, Paris, IDF 75001, France
Compensation: EUR 95k-120k/year + bonus
Experience level: Lead
Team: Vision AI
Benefits & perks

About this role

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

Deepomatic is hiring a Lead Lead Computer Vision Engineer on the Vision 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.

Deepomatic — Field operations vision AI

Role context: Vision AI · based in Paris · ~100-300 people · Scale-up · LLM/genAI focus: No.

You will own delivery across the AI lifecycle—data and evaluation, modeling or LLM-based features, production rollout, and close collaboration with product and domain experts—with pragmatic ownership and clear stakeholder communication.

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.
Docker

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: Apply from this listing on Ganloss so your candidate profile, optional CV link, and cover note reach the hiring team together.
Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, and Docker.
You have led LLM & generative AI initiatives across teams—setting technical direction, review standards, and rollout plans others could follow.
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.

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What the employer asked for

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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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