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3 hours ago
A Senior Data Scientist will architect AI solutions, owning the full machine learning lifecycle from proof-of-concept to production.
Key Responsibilities:- Operationalise large language models and workflows to automate decision-making and threat response.
- Design, deploy, and maintain multi-agent systems for log analysis, anomaly detection, and incident response.
- Build GenAI solutions and evolve them into production-ready components on cloud platforms using reusable best practices.
- Implement CI/CD pipelines for model training, validation, and deployment with version control systems and cloud pipelines.
- Manage model versioning with data management tools and set up automated testing, rollback procedures, and retraining workflows.
- Automate infrastructure provisioning with Infrastructure as Code tools and develop REST APIs and microservices containerised with containerisation tools.
- Monitor models and infrastructure through monitoring tools; analyse performance and optimise for cost and compliance.
- Bachelor's or Master's in Computer Science, Data Science, AI or related quantitative discipline.
- 4+ years of software development experience, including 3+ years building and deploying AI architectures.
- In-depth knowledge of generative AI fundamentals (LLMs, embeddings, vector databases, prompt engineering, RAG).
- Hands-on experience with agentic frameworks.
- Strong proficiency in programming languages and production-grade coding for data pipelines and AI workflows.
- Deep MLOps knowledge: CI/CD for ML, model monitoring, automated retraining, and production-quality best practices.
- Extensive cloud experience with cloud services.
- Infrastructure as Code skills with code tools.
- Experience building REST APIs, microservices, and containerization with containerisation tools.
- Solid data science fundamentals: feature engineering, model evaluation, data ingestion.
- Understanding of cybersecurity principles, SIEM data, and incident response.
- Excellent communication skills for both technical and non-technical audiences.
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