1 to 9 of 9 Permanent Neural Network Jobs in England with Remote Work Options

SizeSutra. As an AI Engineer, you will be responsible for developing and implementing AI algorithms and models, conducting research in pattern recognition and neural networks, and contributing to software development projects. This is a hybrid role, based in the London Area with flexibility for remote work. Qualifications Strong … background in Computer Science, including knowledge of pattern recognition and neural networks Experience in software development, with proficiency in relevant programming languages (e.g., Python, Java) Familiarity with Natural Language Processing (NLP) techniques and frameworks Ability to design and optimize AI algorithms and models Strong problem-solving and analytical more »

of these areas). You will look at the latest development within ML and design and deliver these across ML and Neural Network Methodologies. You will be involved in data analysis and statistical modelling. You will be writing high quality code and deploying these models both on more »

Strong Python skills and understanding of data science and machine learning concepts and algorithms such as clustering, regression, classification, forecasting/predictive analytics, neural networks, hyperparameter tuning, NLP, and utilising LLMs. - **Communication:** Strong ability to communicate complex technical concepts to diverse audiences effectively. - **Management:** Previous line management experience. more »

with numerous publications at prestigious conferences. As a Research Engineer, you'll collaborate globally to tackle complex deep learning challenges, focusing on graph neural networks and pioneering new foundation models in healthcare. The Impact Your research will directly contribute to real-world applications with a profound social impact more »

well as a deep understanding of how to implement solutions using Retrieval Augmented Generation (RAG) architecture. Expertise in graph machine learning (i.e. graph neural networks, graph data science) and practical applications thereof. This is complimented by your experience working with Knowledge Graphs, ideally biological, and a familiarity with more »

understanding of the Retrieval Augmented Generation architecture and ideally deploying solutions leveraging RAG. GML/GNNs: expertise in graph machine learning/graph neural networks and practical applications. Technical expertise: Comprehensive knowledge of software engineering and industry experience using Python. Domain: ideally worked in the biological/science more »

generalized linear models, logistics/linear Regression, Tree based and Boosting models, Decision trees, Random Forest, XGBoost etc.- Basic understanding of Neural network and deep learning models). Possess experience with Machine learning/Pattern recognition areas. Should possess basic Data Engineering experience to ingest, cleanse and more »

an integral part of a growing team (20 to 40 people in 12 months!) Tech skills needed for this ML engineering role: Deep Neural Networks (DNN) Generative Adversarial Networks Deep Learning Define, evaluate and assess AI systems performance Explore and implement state-of-the-art algorithms to keep more »

following predictive modelling techniques e.g. Logistic regression, Log-Gamma GLMs, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Support Vector Machines and Neural Nets. Experience of Emblem and Radar. Experience in the use of programming language such as Matlab and Python. Very strong planning, prioritisation and organisational more »