Our client a London based Technology and Data Engineering leader have an opportunity in a high growth AI Lab for an ‘AI Engineering Researcher' A UK based 'Enterprise' Artificial Intelligence organisation, focussing on helping accelerate their clients journey towards becoming 'AI-Optimal' - starting with significantly enhancing its abilities in leveraging AI & machine intelligence to outperform traditional competition. The firm builds upon its rapidly expanding research team of exceptional PhD computer scientists, software engineers, mathematicians & physicists, to use a unique multi-disciplinary approach to solving enterprise-AI problems. Principal Activities of role: Data Pipeline Development: • Design, develop, and maintain ETL processes to efficiently ingest data from various sources into data warehouses or data lakes. • Data Integration and Management: Integrate data from disparate sources, ensuring data quality, consistency, and security across systems. Implement data governance practices and manage metadata. • System Architecture: Design robust, scalable, and high-performance data architectures using cloud-based platforms (e.g., AWS, Google Cloud, Azure). • Performance Optimization: Monitor, troubleshoot, and optimize data processing workflows to improve performance and reduce latency. Typical background: − Bachelor’s or Master’s degree in computer science/engineering/Math/Physics, plus one or more of the following: − Proficiency in programming languages such as Python, Java, or Scala. − Strong experience with SQL and database technologies (incl. various Vector Stores and more traditional technologies e.g. MySQL, PostgreSQL, NoSQL databases). − Hands-on experience with data tools and frameworks such as Hadoop, Spark, or Kafka - advantage − Familiarity with data warehousing solutions and cloud data platforms. − Background in building applications wrapped around AI/LLM/mathematical models − Ability to scale up algorithms to production Key Proposition: - This role offers the opportunity to be part of creating world-class engineered solutions within Artificial Intelligence / Machine Learning, with a steep learning curve and an unmatched research experience. Time Commitments: 100% (average 40 hours per week)