AI role · Open offer

Computer Vision Engineer — Industrial QA

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Focus: Data Labeling AI

Paris · 50-200 employees · Startup · GenAI: No

Permanent (CDI)
Senior
Vision systems
Hybrid
Lyon, France · Hybrid
€72k–€92k

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)
Workplace: Hybrid
Location: Lyon, France · Hybrid
Compensation: €72k–€92k
Experience level: Senior
Team: Vision systems
Benefits & perks

About this role

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

Kili Technology is hiring a Senior Computer Vision Engineer — Industrial QA on the Vision systems team (Hybrid · Lyon, France). This is a hands-on role in computer vision & geospatial AI—not a generic “AI enthusiast” post.

You will own vision, sensor, or geospatial models in production 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.

Lyon plant-floor AI squad delivers defect detection for automotive suppliers. You will iterate quickly with quality engineers while meeting strict traceability for ISO programs.

Hybrid with regular site visits; PPE and safety training provided.

What you will do

Own CV model lifecycle: datasets, labelling QA, training, quantisation, deployment.
Tune lighting/camera recommendations with maintenance teams.
Instrument false-positive/false-negative reviews for continuous learning loops.
Produce validation packets for customer quality audits.
Mentor junior CV engineers on robust augmentation strategies.

What we look for

4+ years industrial CV—not only academic benchmarks.
PyTorch proficiency; deployment to edge or near-edge targets.
Willingness to travel regionally within France.

Nice to have

Thermography or 3D vision experience.
MES/SCADA integration familiarity.

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

Tools & stack

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

AWSTool
Regular use of AWS in the computer vision & geospatial 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: One example of quantization or ONNX tradeoffs you chose.
Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, Docker, and AWS.
You have owned vision, sensor, or geospatial models in production in production: debugging live issues, running postmortems, and iterating from real user or business signals.
You are comfortable with the hybrid rhythm (Hybrid · Lyon, 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: €72k–€92k, benefits in At a glance) and your expectations align.

Apply

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What the employer asked for

One example of quantization or ONNX tradeoffs you chose.

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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