1 to 25 of 44 Permanent Neural Network Jobs in the UK

We are looking for a goal oriented and driven AI/ML Engineers with relevant experiences. Key Responsibilities: Neural Network Training : Develop and train advanced neural network models to meet specific functional requirements. Deployment and Integration : Efficiently deploy these neural networks on … trends. Skills and Qualifications: Minimum 2 years of experience in building AI/ML software. Strong expertise in machine learning and neural network algorithms. Proficient in programming languages like Python, and frameworks such as TensorFlow or PyTorch. Experience with server deployment, cloud computing environments, and API development. more »

Performance Tools Engineer in Cambridge, UK About Neubla As pioneers of innovative neural computing, Neubla is transforming the future of computing by bringing the enormous potential of neural computing to the highest performance in most data-intensive applications. Neubla is made up of people with expertise … CPU. However, in AI accelerator domain, the performance model has often been taken lightly due to the regular computation patterns of neural network models. However neural network models are getting bigger and much more complex every month, and it became almost impossible to estimate more »

client delivers systems that can perceive and understand the world with the same semantic richness as the human brain and using the same neural mechanisms they believe are at work in the brain. Their approaches are inspired by their recent advances in theoretical neuroscience, which are beginning to … how the brain makes sense of the world. The project team will work on the development of a novel enhanced convolutional neural network based on a proprietary approach already developed by the company. Applied Computer Vision Data Scientist - job responsibilities: Enhance our machine learning software with the …/computer vision algorithms. Apply existing knowledge of Transformers and CNNs, machine vision & image analysis techniques to the development of enhanced neural network systems based on our research outputs. Work to customise and implement our machine learning solutions for use by prestigious and demanding customers. Contribute to more »

to unlock valuable insights. Responsibilities Spearhead projects with cross functional leaders Use models like regression and propensity models, time-series, ensemble methods and neural networks Seek out opportunities to make an impact using the latest ML methods (NLP and Gen AI) Be the go-to authority for data more »

Science, Mathematics, Statistics, Physics, Engineering, or a related field. Strong background in deep learning, with hands-on experience in developing and implementing deep neural networks using frameworks such as TensorFlow, PyTorch, or Keras. Proficiency in programming languages such as Python and experience with data manipulation and analysis libraries more »

testing, and regression. Skilled in employing advanced machine learning algorithms and statistical techniques like regression, simulation, scenario analysis, modelling, clustering, decision trees, and neural networks to address business challenges. Demonstrated track record of applying statistical modelling and machine learning in industrial settings. Experience mentoring junior team members If more »

testing, and regression. Skilled in employing advanced machine learning algorithms and statistical techniques like regression, simulation, scenario analysis, modelling, clustering, decision trees, and neural networks to address business challenges. Demonstrated track record of applying statistical modelling and machine learning in industrial settings. Experience mentoring junior team members If more »

and Large Language Models (LLMs). Knowledge of distributed computing and cloud platforms (AWS, Azure, or Google Cloud). Research experience in Graph Neural Networks would be a plus. Strong publication record in relevant conferences or journals. Benefits (Remote must be within 4-5 hours of CET timezone more »

selection, PCA, hypothesis testing, time series, queuing theory, survival analysis, clustering, linear programming. Experience with machine learning methods, such as regularization, random forests, neural networks and deep learning. Ability to write algorithms and implement pipelines in Python. Knowledge of Scala, R, is a plus. Experienced in SQL. Familiarity more »

Science or Robotics. Relevant publications or talks at industry conferences or in journals. Developed machine learning applications in Python. Experience with compilers for neural networks. Experience developing and fielding autonomous systems. Familiarity with Google Cloud Platform. The Candidate Journey: Multi-Step and Two-Way No-one wants to more »

business problems, using coding in SAS/Python/R or similar Have deep knowledge of different advanced techniques, such as Gradient Boosting, Neural Networks, Support Vector Machines, unsupervised learning methodologies etc., including of their merits and limitations Have hands-on experience of leading, motivating and mentoring a more »

Your meticulous attention to detail ensures data quality and integrity throughout the preprocessing phase. You excel in training and fine-tuning neural network-based language models, leveraging large-scale text corpora to optimise model performance for specific NLP tasks. Your experience extends to selecting appropriate model architectures … for specific NLP tasks through exploratory data analysis (EDA) and validation against ground truth or domain knowledge. Demonstrated experience in training neural network-based language models from scratch using large-scale text corpora. Proficiency in selecting appropriate model architectures, hyperparameters, and training strategies to optimize model performance more »

such as numpy, pandas, and scikit-learn Experience with deep learning frameworks (PyTorch, JAX, Keras, Tensorflow) Strong theoretical understanding of machine learning and neural networks Experience with containerized processes (Docker, Kubernetes) Familiarity with cloud services and distributed computing frameworks (AWS, PySpark, Ray Distributed) Problem-solving aptitude and creative more »

with the ability to write algorithms with ease. Good understanding of data science and machine learning fundamentals like regression, classification, tree-based approach, neural networks, and sequence-based models. Experience with advanced machine learning techniques, including LLM and generative AI for generating high-quality metadata and artwork. Proven more »

or home pricing Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering. Knowledge of the technical differences between different packages for some of these model types would be an advantage. Experience in statistical more »

and industry-leading computing tools to apply and build ML models from the ground up, utilizing new and established techniques and methods like neural networks, reinforcement learning, deep learning, and natural language processing. Remain connected to the broader research community, staying on top of the latest research and more »

The Role: Your day-to-day responsibilities will include: Working on core segmentation, churn, and recommender system-based projects, alongside deep learning and neural networks to support core clients Part of a team of 8 reporting to the Head of Data Science - working closely with a wider Engineering more »

Proficiency in Python Strong NLP experience – NumPy, Pandas etc. Commercial experience leveraging open-source models, finetuning LLMs & RAG pipelines Expertise in learning algorithms, neural networks and ML frameworks (TensorFlow, PyTorch etc.) MLOps experience Nice to have: Familiarity with Git or other Version Control Systems Computer Vision Library exposure more »

features, NumPy, keras, pandas, NLTK, scikit, SpaCy > Machine Learning NLP, ML algos, Hugging Face, large language models (LLMs), Retrieval Augmented Generation), learning algorithms, neural networks, ML frameworks (TensorFlow, PyTorch) > Strong IaC experience, using Terraform or CloudFormation > Data Wrangling > Systems: Linux, APIs, infrastructure design load balancing, VMs, PostgreSQL, vector more »

applying feature analysis to identify key areas to maximise effectiveness inc. Permutation Importance. Utilising machine learning methodologies such as tensorflow/keras. Creating neural networks, optimising layer structures and learning rates, and working to improve model efficiency. Performing deep dives into online user interaction data to ensure we more »

Engineer Strong foundation in Python Excellent knowledge of ML libraries and frameworks like TensorFlow, PyTorch, Keras and scikit-learn. Experience with neural network architectures, deep learning techniques, and building and training deep learning models. Creating and handling large datasets including pre-processing steps and familiarity with data more »

batch and real-time prediction scenarios: Use machine learning and statistical modeling techniques such as Reinforcement Learning,Decision Trees, Logistic Regression, Bayesian Analysis, Neural Networks and others to develop and evaluate algorithms to improve product/system performance, quality and accuracy Low level systems debugging, performance measurement & optimization more »

in a collaborative and entrepreneurial environment with great opportunities for career progression. Responsibilities: Apply the rigorous scientific method and methods such as NLP, neural networks and deep learning to develop sophisticated trading models across multiple asset classes that inform highly profitable trading strategies. Work with an elite group more »

Data Scientist that wants to design and push boundaries in the Remote Sensing and Environmental space using Python, Deep learning/ML and Neural networks and ideally some experience practically developing learning in Computer Vision Our clients mission is to empowers efforts to heal ecosystems globally. We champion more »

to solve real world financial problems Build/run in-house developed and third party ML models in production Deep learning research (Graph Neural Networks) Natural language processing (Semantic search, Generative LLMs) Datapoint extraction Develop novel methods to facilitate financial research from unstructured data. We are a research more »