AI Engineer, Netcraft

• Advanced knowledge of machine learning, deep learning, and statistical analysis. Massive bonus points if you have experience applying these skills to threat detection, malware analysis, phishing, and/or abuse detection
• Experience designing and implementing anomaly detection, classification, clustering, and retrieval across vision and
• Language models, ideally for identifying cyber threats (URLs, domains, phishing, botnets, etc.)
• Hands-on experience building production-grade AI pipelines, including data ingestion, feature engineering, validation, model deployment, and monitoring
• Proficient in a major backend language and related ML/AI libraries (e.g. Tensorflow & PyTorch, etc), with a preference for Go
• Experience with an MLOps platform like Kubeflow
• Demonstrated ability to transition models from prototype to production
• Experience assessing various AI/ML technologies and models for fit to problem space, including scenarios where RAG is applicable
• Incident response experience, and ability to work with large, noisy, and rapidly evolving threat datasets
• Strong background in cloud engineering and containerisation (Docker, Kubernetes), with experience deploying AI services at scale, particularly on AWS via Terraform

Desirable

• A senior/principal AI Engineer at Netcraft should combine deep applied AI/ML expertise, a hands-on and collaborative approach to developing solution architecture, and eventually develop a strong domain knowledge in cyber threat detection and mitigation.
• The role is highly collaborative, embedding within technical teams to deliver robust, explainable, and impactful AI-based solutions that advance threat detection efficacy and enable Netcraft to continue to scale
• Collaboratively designing, training & deploying end-to-end AI systems and rapidly prototyping
• New approaches to detecting phishing, fraud & scams
• Improving existing implementations with state-of-the-art models and optimisations
• Integrating AI services into production environment using Go (Golang) and occasionally Perl
• Collaborative and cross-functional, with a proven track record of working with diverse teams to deliver projects
• Comfortable learning teams' services and workflows, and capable of mentoring and engaging in knowledge transfers. The intent is to help embed patterns and best practices across multiple teams
• Cost-aware, and able to articulate
• Business benefits against the often-high run cost of at-scale AI/ML services
• On top of the latest developments in the industry, and able to advise on new and alternative approaches to solving problems
• Lead Day 2 monitoring & analysis of models