1 to 25 of 27 Neural Network Jobs in London

optimising algorithms and models. Predictive modelling techniques for regression and classification. Time series analysis for handling time-dependant data. Deep learning and neural networks. LLM Operations Expertise in managing and operationalising large language models. Experience in deploying models on cloud platforms (e.g. AWS, Sage maker, Google AI Platform ...

PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research in machine learning are also beneficial. Experience configuring and maintaining cloud infrastructure including network infrastructure, compute, access control ...

needle. Machine Learning Engineer, LLM Engineer, AI Engineer, Artificial Intelligence, Deep Learning, NLP, Natural Language Processing, Large Language Models, Generative AI, GenAI, Neural Networks, PyTorch, TensorFlow, Hugging Face, OpenAI, LangChain, RAG, Retrieval-Augmented Generation, Python, Data Science, AI Research, MLOps, Data Pipelines, Prompt Engineering, Model Fine-Tuning, Cloud ...

includes: Familiarity with CUDA and optimising highly parallelised GPU-based computations are a plus Familiarity with the end-to-end supervised training of neural networks and accompanying MLOps ecosystem are a plus Familiarity with Django and related frameworks/tools Familiarity with other programming languages and frameworks ...

Building data pipelines (real-time or batch) using tools like Apache Spark, Kafka, Airflow, or dbt Familiarity with recommender systems, transformers, or graph neural networks Exposure to model optimisation techniques (quantisation, distillation, efficient inference) What We Offer Opportunity to build technology that will transform millions of shopping experiences. ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

salaries, flexible working arrangements, and genuine job security. How It Works Step 1 – AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 – Data Fundamentals Understand the data workflow, from collection ...

large, intricate datasets. Nearly hundreds of global partners rely on this platform to make confident automated decisions informed by advanced forecasting and deep neural networks. Here your work won’t sit in a research silo, your models will directly influence sophisticated, live operational systems. The environment values intellectual … deep learning - demonstrated through publications in top-tier journals and conferences (NeurIPS, ICML, ICLR, JMLR, etc.). Strong experience with neural network models applied to time series, dynamic forecasting, and complex sequential tasks. Industry experience implementing and refining forecasting systems in production. Proficiency in modern ML frameworks ...

delivery approach and outcomes Technology environment Python Databricks Large scale and streaming data Spark or Kafka style processing Tree based models and deep neural networks Production grade machine learning systems What my client look for Essential experience Senior level data science delivery Large scale or time series data ...

cross-functional teams to identify challenges and implement innovative solutions tailored to the organization’s needs. Qualifications Strong expertise in Pattern Recognition and Neural Networks Proficiency in Computer Science and Software Development Experience in Natural Language Processing (NLP) techniques and applications Proven problem-solving and critical thinking skills ...

Complete end-to-end experience - from finding and cleaning data all the way to monitoring models in production Strong understanding of neural networks, CNNs, RNNs, LSTMs, and transformers Experience building automated data pipelines Hands-on experience with LLM tooling and libraries (e.g., Hugging Face Transformers/PEFT, tokenisers ...