AI / Data Science Engineer

Title: AI / Data Science Engineer

Contract Duration:  Permanent

Work Location: Greater London, UK

 

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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