AI / Data Science Engineer

🔒 Confidential Employer
Posted 28 April 2026
LOCATION
Greater London
TYPE
Contract
LEVEL
Mid-Senior level
CATEGORY
AI / Data Science
This employer holds a UK Home Office sponsor license — sponsorship for this specific role is at the employer’s discretion

SKILLS

Generative AI Computer Vision Natural Language Processing Audio Processing Azure AI Studio Edge Impulse Python SQL

FULL DESCRIPTION

AI / Data Science Engineer

Company: [Employer hidden — view at passion-project.co.uk]

Location: Greater London, UK

Job Type: Contract

Work Type: On-site

Job Description

As an AI Data Engineer, you must have:

  • A track record of AI and Data solutions, with practical experience implementing these technologies to create productized solutions.
  • Proficiency in hands-on development of end-to-end AI solutions, spanning a broad spectrum of AI domains, including Generative AI, Computer Vision, Natural Language Processing, Audio Processing, and Expert Systems.
  • Demonstrated expertise in utilizing standardized AI services such as Azure’s AI Studio and Edge Impulse to construct scalable AI solutions.
  • Proven experience crafting and deploying AI solutions in cloud and Edge environments, focusing on leveraging AI to enhance IoT capabilities.
  • Experience managing substantial volumes of IoT device and telemetry data by constructing robust data platforms.
  • A solid grasp of machine learning principles across various methodologies, encompassing regression, clustering, and nearest neighbour techniques, with a keen awareness of data quality, bias, tagging, and data modelling considerations.
  • Competence in developing data analytics solutions capable of extracting valuable insights from diverse data types, including images, audio, video, and time series data, particularly from IoT and product datasets.
  • Experience evaluating technologies and vendor offerings within the data and AI landscape.
  • Familiarity with Data and AI platforms and their underlying infrastructure, such as Azure IoT, AWS, Google Cloud, etc.
  • Proficiency in comprehending the various architectural layers of data and AI systems, from data collection and ingestion to processing, storage, and visualization.
  • A strong background in multiple cloud platforms, with a specific focus and practical experience in the Microsoft Azure ecosystem, especially within the data and AI service domain.
  • Robust software development skills in languages such as Python, SQL, MQL, JavaScript, TensorFlow, and PyTorch.
  • A history of utilizing various database technologies, including SQL Server, MongoDB, Cassandra, PostgreSQL, Redis, and MySQL.
  • Knowledge of Cloud Native open standards technologies and secure software architectures.
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