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Tech Stack
Tools & technologiesAWSAzureCloudCyber SecurityDockerGoogle Cloud PlatformJavaKubernetesPythonPyTorchScikit-LearnSQLTensorflow
About the role
Key responsibilities & impact- Prototype & Deploy AI Solutions: Develop proof-of-concepts for cybersecurity use cases (e.g., anomaly detection, LLM-based threat intelligence analysis, cyber risk agent, automated incident response).
- LLM & Generative AI: Build RAG systems, knowledge graphs, or agentic workflows to extract for example insights from security logs, threat feeds, or internal documentation.
- Model Development: Fine-tune and deploy ML/DL models for tasks like malware classification, phishing detection, or user behavior analytics.
- Cloud & MLOps: Engineer scalable, secure AI pipelines on Azure/GCP/AWS, from data ingestion to model serving (Docker, Kubernetes, CI/CD).
- Collaborate with Security Teams: Partner with SOC analysts, threat hunters, and IT teams to translate security challenges into AI-driven solutions.
- Innovate Continuously: Research and integrate emerging AI/ML techniques (e.g., adversarial ML, federated learning) to stay ahead of evolving threats.
Requirements
What you’ll need- Experience: 2+ years as a Data Engineer, AI Engineer, or similar role, with a focus on applied AI/ML (cybersecurity experience is a strong plus).
- Education: Bachelor’s or Master’s in Computer Science, Data Science, Cybersecurity, or related field.
- Programming: Strong Python skills (PyTorch, TensorFlow, scikit-learn). SQL, Java, or C++ are assets.
- AI/ML: Hands-on experience with LLMs (fine-tuning, RAG, prompt engineering), embeddings, and traditional ML/DL models.
- Cloud: Proven experience deploying AI solutions on Azure, GCP, or AWS (certifications are a plus).
- Tools: Familiarity with MLOps (MLflow, Kubeflow), APIs, Git, Docker/Kubernetes.
- Cybersecurity Awareness: Understanding of cyber threats, data privacy, and secure coding practices (experience with SIEM/EDR tools is a plus).
- Languages: Fluent English (written and spoken) is mandatory. French is a strong plus.
Benefits
Comp & perks- High impact: Your models will secure global operations against evolving cyber threats.
- Innovation: Work with LLMs, Generative AI, and emerging technologies in a dynamic environment.
- Growth: Access to training, certifications, and conferences.
- Team: Join a multidisciplinary group of AI and cybersecurity experts.
ATS Keywords
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Hard Skills & Tools
PythonPyTorchTensorFlowscikit-learnSQLJavaC++LLMsMLOpsML/DL models
Soft Skills
collaborationcommunicationproblem-solvinginnovationresearch