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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)