Senior AI/ML Engineer, Security Log Intelligence

RedMimicry GmbH · Berlinsenior

En corto

▸Desarrollas modelos de IA/ML para transformar logs de seguridad caóticos en análisis de amenazas explicables.
▸Tu trabajo diario combina ingeniería de producción, evaluación rigurosa y diseño de sistemas que operan bajo restricciones reales de latencia y fiabilidad.
▸Destaca que debes entregar mejoras medibles frente a benchmarks reproducibles, no solo usar tecnologías de moda.

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¿Qué piden?

✓Fortes habilidades en Python y PyTorch o framework comparable.
✓Experiencia práctica con modelos de lenguaje abiertos, embeddings, recuperación de información o sistemas de inferencia.
✓Capacidad para evaluar modelos usando métricas como Recall@K, F1, MRR y análisis de fallos.
✓Experiencia en convertir código experimental en componentes productivos y mantenibles.
✓Conocimiento de logs de seguridad (SIEM, EDR, NDR) y telemetría de sistemas.
✓Capacidad para documentar decisiones técnicas y contribuir a publicaciones académicas.

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

PythonPyTorchopen-weight language modelsstructured outputsembeddingsretrieval systemsPEFTquantisationmodel servinginference optimisation

¿A quién escribirle en RedMimicry GmbH?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

We are building a new capability that turns fragmented, noisy security logs into explainable, AI-powered threat analysis, delivered inside the RedMimicry platform. As Senior AI/ML Engineer at RedMimicry, you will lead the applied AI/ML work behind new analysis capabilities for our breach and attack emulation platform. The core challenge is extracting useful structure from heterogeneous, partially unstructured security telemetry and relating it to known attacker activity. The problem is broader than prompt engineering. You will determine where LLMs, embeddings, retrieval, learned ranking, and deterministic heuristics are justified. The standard is measurable improvement against reproducible baselines, not architectural fashion. Everything you build must operate under realistic latency, reliability, and deployment constraints. This is a fixed-term position running until 31 October 2027. Tasks Develop Security-Log Parsing Methods: Design and implement methods for extracting typed events from heterogeneous SIEM, EDR, NDR, operating-system, and network telemetry. Design Embeddings and Retrieval: Select, evaluate, and tune representations and retrieval methods for security events. Handle Ambiguity Explicitly: Implement confidence scoring, calibration, and controlled treatment of ambiguous evidence. Ground Results in Evidence: Ensure that results are supported by traceable evidence from the original telemetry. Build Rigorous Evaluations: Define datasets, baselines, ablations, and metrics, and analyse failure modes systematically. Optimise Inference: Make the pipeline practical for cloud operation and on-premises deployment. Productise the Research: Work with backend, integration, and offensive-security engineers to turn experimental methods into maintainable services. Document the Work: Produce clear experiment records, architecture decisions, and technical reports. Contribute to Academic Research: Contribute, at minimum as a co-author, to an academic research paper published in the context of the project. Requirements You do not need to meet every requirement to apply. We care more about demonstrated depth, sound experimental judgement, and the ability to ship reliable systems than about a specific academic title. Benefits Work from anywhere in Germany, and use our Berlin office as often as you like 30 days of paid time off, and a quiet inbox while you are away Company-paid Deutschlandticket Annual budget for the courses and certifications you pick yourself Modern tooling and extensive use of AI Ligh

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