6 of 6 Contract Deep Learning Jobs in the UK excluding London

Machine Learnig Engineer Hybrid Working - UK Wide - 1 day a quarter on site. Financial Services Lorien's leading banking client is looking for a Machine Learning Engineer to join the growing data science and AI team. You'll play a key role in designing, developing, and deploying scalable machine learning solutions using Python and Amazon SageMaker . This … role is based UK Wide. This role will be Via Umbrella. Working in a Hybrid Model of 1 day a week on site. Key Responsibilities Design and implement machine learning models for classification, regression, and forecasting tasks. Build and manage end-to-end ML pipelines using Amazon SageMaker . Collaborate with data scientists, engineers, and product teams to integrate … ML/data libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow or PyTorch). Hands-on experience with Amazon SageMaker , including training, tuning, and deploying models. Solid understanding of machine learning algorithms and statistical methods. Experience with cloud platforms (AWS preferred). Familiarity with CI/CD practices and version control (Git). Excellent problem-solving and communication skills. Nice More ❯

to ensuring seamless integration with existing digital services. What You'll Need to Succeed Commercial experience with AI/ML technology: OCR, Object Detection and LLM analysis implementation * Machine Learning & AI Libraries including: o Transformers/Hugging Face for working with pre-trained LLMs, fine-tuning, and inference o PyTorch for deep learning model development and training More ❯

to ensuring seamless integration with existing digital services. What You'll Need to Succeed Commercial experience with AI/ML technology: OCR, Object Detection and LLM analysis implementation * Machine Learning & AI Libraries including: o Transformers/Hugging Face for working with pre-trained LLMs, fine-tuning, and inference o PyTorch for deep learning model development and training More ❯

/Engineering, or related disciplines. Proficiency in mathematics (calculus, probability, statistics, linear algebra, optimization) and computer science (algorithms, data structures, parallel/distributed computing). Strong fundamentals in Machine Learning, Computer Vision, and Deep Learning. Hands-on experience in areas such as Generative AI, Foundation Models, Parameter-Efficient Fine-Tuning (PEFT), Data/Model Privacy, or Model Optimization …/journals (e.g., ICML, NeurIPS, ICLR, CVPR, ECCV, IEEE TPAMI, AAAI). Experience in Linux environments. Proficiency in programming languages such as Python, Java, or C++. Experience with machine learning libraries like PyTorch, SciKit, NumPy, etc. Excellent communication skills, teamwork abilities, and a results-oriented attitude. Strong problem-solving and debugging skills. Desirable Skills: Expertise in Image/Video More ❯

to the global research community Who You Are: A PhD holder in ML/AI, Computer Science/Engineering, or a related field. A strong foundation in Mathematics, Machine Learning, NLP, and Deep Learning. Hands-on experience in one or more of these areas: Generative AI, Parameter-efficient Fine-tuning, Model Compression, Foundation Models, Large Language Models (LLMs …/AI conferences/journals (e.g., ICML, NeurIPS, ICLR, EMNLP, CVPR, ECCV, IEEE TPAMI, AAAI). Proficient in programming languages like Python, Java, or C++, and experienced with Machine Learning libraries (e.g., PyTorch, SciKit, NumPy). Comfortable working in Linux environments and collaborating in a hybrid team setup. Exceptional communication, teamwork, and problem-solving skills. Why Join Us? Be More ❯

GitHub Copilot for development. Ensure responsible AI practices aligned with NIST AI RMF , EU AI Act , and other ethical standards. Mentor junior developers and foster a culture of continuous learning and innovation. Skills & Experience 10+ years in software engineering, with strong experience building cloud-native or platform services using Microsoft and .NET . 4+ years in a Data Scientist … or AI/ML Engineer role. Proficiency in Python , including libraries like pandas , scikit-learn , TensorFlow , and PyTorch . Deep understanding of ML algorithms : regression, classification, clustering, and deep learning. Hands-on experience with Large Language Models (LLMs) and techniques such as Retrieval-Augmented Generation (RAG) , agent orchestration , prompt engineering , and tool calling . Familiarity with AI standards More ❯