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Senior AI Developer — defense systems
Thales
Este anuncio está pensado para talento nativo en IA : habilidades y herramientas claras para saber si encajas antes de aplicar — y para reducir descartes por desajuste.
4 habilidades 2 herramientas
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Empleo
Modalidad Hybrid
Ubicación 6 Rue de la Redoute, 95100 Argenteuil, France · Hybrid
Compensación EUR 65k–90k/year + intéressement Nivel de experiencia Equipo Beneficios Mutuelle, hybrid IDF, security clearance support. Cómo aplicar LLM or CV for mission-critical systems with safety documentation.
Publicada 4 dic 2026 Thales is hiring a Senior Senior AI Developer — defense systems on the Critical systems AI team (Hybrid · Argenteuil, 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.
Thales designs mission-critical systems for aerospace, defense, and digital identity — with a major Île-de-France engineering presence in Argenteuil .
Senior AI Developer (hybrid Argenteuil): LLM assistants , sensor fusion , and computer vision for regulated environments with formal safety cases.
About Thales
Global defense and aerospace leader with French roots since 1893. Argenteuil site focuses on secure communications and critical software. AI work must meet export-control and security clearance requirements. What you will do
Prototype copilots for operator workflows with audit trails. Validate models against adversarial and edge-case test suites. Document model lineage for certification reviewers. Stack & environment
Python, PyTorch, LangChain, on-prem Kubernetes, air-gapped deploys. Hybrid Argenteuil; French and English engineering teams. What we look for
5+ years applied ML/LLM; defense or avionics experience valued. Eligible to work in France; clearance process supported. 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.
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).
Docker Tool
Containerized services and reproducible dev environments for ML and LLM workloads.
Kubernetes Tool
Deploying and scaling model services with health checks, autoscaling, and rollout discipline.
✓ You can show evidence in your application: LLM or CV for mission-critical systems with safety documentation. ✓ Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, LangChain, Computer Vision, and Docker. ✓ 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 · Argenteuil, 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 65k–90k/year + intéressement, benefits in At a glance) and your expectations align. Lo que pide la empresa
LLM or CV for mission-critical systems with safety documentation.
Inicia sesión con cuenta candidato para aplicar
Regístrate, añade titular y bio; luego podrás adjuntar enlace o PDF de CV en Mi cuenta antes de aplicar. Así las candidaturas quedan ligadas a tu perfil.
Sugerencias
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Título
Senior AI Developer — defense systems
Aplicar Pensado para equipos que contratan personas que trabajan con IA, no solo alrededor.
Los candidatos ven habilidades y herramientas al inicio; recibes candidaturas estructuradas en un solo panel.
Llega a profesionales de IA que buscan roles con expectativas basadas en pruebas.
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