Lead AI Research Engineer at AVEVA, focusing on prototyping and validating emerging AI technologies. Collaborating with teams to drive innovation and real - world applications in industrial software.
About the role
- Senior AI Scientist driving innovation in advanced AI systems for Euromonitor. Leading projects from research to model refinement across various AI technologies.
Responsibilities
- Design and prototype advanced AI models, including NLP, computer vision, and multimodal architectures
- Build and validate LLM‑based solutions, including retrieval‑augmented generation (RAG), prompting frameworks, and fine‑tuned models
- Develop proof‑of‑concept pipelines across supervised, unsupervised, and semi‑supervised tasks
- Translate domain and industry knowledge into scalable AI techniques
- Conduct data quality monitoring, exploratory analysis, and feature engineering
- Communicate AI findings clearly through written narratives, visuals, and presentations
- Collaborate with Data Scientists, AI Engineers, Product teams, and stakeholders
- Ensure models are robust, maintainable, and compatible with existing production ecosystems
Requirements
- Strong proficiency in Python (or R) and SQL
- Familiarity with PyTorch, TensorFlow, Hugging Face, and related AI stacks
- Experience with Google Cloud Platform (GCP); Azure is a plus
- Ability to build and maintain cloud resources (notebooks, buckets, SQL instances, VMs, service accounts)
- Experience with git workflows, merge requests, and code review
- Understanding of CI/CD pipelines, scripting, shell commands, and automation
- Awareness of model scaling, cost optimisation, and experiment tracking tools
- Strong ability to select appropriate visual techniques for text, images, and numeric data
- Proficiency with at least one visualisation or dashboarding framework
- Capable of producing shareable or dynamic reports/apps
- Strong understanding of EDA, classical ML methods, clustering, and predictive modelling
- Applied experience with NLP, embeddings, and text‑based workflows
- Ability to maintain and improve ML models
- Hands‑on experience with LLM‑based workflows (e.g., LangChain or similar frameworks)
- Knowledge of prompt patterns, failure modes, and evaluation strategies
Benefits
- Flexible work time with the perfect work/life balance
- Competitive salary with wide variety of benefits like longer holidays, additional health insurance, social responsibility initiatives you can take part in, office perks
- Intelligent and fun colleagues working in a constructive and inspiring atmosphere
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