Artificial Intelligence - Deep Learning Engineer
| Dyddiad hysbysebu: | 30 Mehefin 2025 |
|---|---|
| Cyflog: | £54,423 i £59,898 bob blwyddyn |
| Oriau: | Llawn Amser |
| Dyddiad cau: | 30 Gorffennaf 2025 |
| Lleoliad: | B18 6BA |
| Gweithio o bell: | Hybrid - gweithio o bell hyd at 3 ddiwrnod yr wythnos |
| Cwmni: | DEVI TECHNOLOGIES LIMITED |
| Math o swydd: | Parhaol |
| Cyfeirnod swydd: |
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Create systems based on neural networks that can learn and make decisions from large amounts of data.
Use powerful computing tools to teach the system using data, and test how well it performs.
Prepare, clean, and organize data (e.g., images, videos, or text) for training deep learning models.
Improve how fast and accurately the models learn and perform tasks.
Work with data scientists, software engineers, and product teams to deliver AI solutions that solve real-world problems.
Learn and apply the latest deep learning research, tools, and techniques.
Strong skills in Python programming
Experience with deep learning frameworks like TensorFlow, PyTorch, or Keras
Solid understanding of neural networks, convolutional networks (CNNs), and recurrent networks (RNNs)
Good knowledge of mathematics, especially linear algebra, probability, and calculus
Ability to handle large datasets and use tools such as NumPy, Pandas, or OpenCV
Experience with computer vision, natural language processing (NLP), or speech recognition
Familiarity with GPU computing and tools such as CUDA for model training
Knowledge of MLOps and deploying deep learning models into real-world applications
Experience working with cloud services (e.g., AWS, GCP, Azure)
Use powerful computing tools to teach the system using data, and test how well it performs.
Prepare, clean, and organize data (e.g., images, videos, or text) for training deep learning models.
Improve how fast and accurately the models learn and perform tasks.
Work with data scientists, software engineers, and product teams to deliver AI solutions that solve real-world problems.
Learn and apply the latest deep learning research, tools, and techniques.
Strong skills in Python programming
Experience with deep learning frameworks like TensorFlow, PyTorch, or Keras
Solid understanding of neural networks, convolutional networks (CNNs), and recurrent networks (RNNs)
Good knowledge of mathematics, especially linear algebra, probability, and calculus
Ability to handle large datasets and use tools such as NumPy, Pandas, or OpenCV
Experience with computer vision, natural language processing (NLP), or speech recognition
Familiarity with GPU computing and tools such as CUDA for model training
Knowledge of MLOps and deploying deep learning models into real-world applications
Experience working with cloud services (e.g., AWS, GCP, Azure)
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