1 to 25 of 85 Permanent Neural Network Jobs in the UK

turn ideas into reality. If you're passionate about pushing the boundaries of AI, we want you on board! Job Description We are seeking an experienced Neural Network Optimization Engineer who will specialize in enhancing the performance, latency, and throughput of neural network inference workflows. The ideal candidate will have substantial hands-on experience … You will collaborate closely with ML researchers to ensure that our machine learning models run at peak efficiency and reliability in production environments. Key Responsibilities Optimize neural network models for inference performance and latency reduction Benchmark, analyze, and improve inference performance on targeted hardware platforms. Collaborate with the ML researchers to deploy optimized models in production environments. … Stay updated with the latest developments in model optimization, inference engines, quantization methods, and related technologies. Requirements Proven professional experience optimizing neural network inference workloads. Strong expertise with TensorRT, Triton language, CUDA programming. Experience with neural network quantization techniques. Proficiency in Python and PyTorch. Deep understanding of GPU architectures and performance optimization. Excellent problem More ❯

Visual Computing Group (VCG) and contribute to redefining the world of game play and live streaming via advanced R&D. VCGs mission is to design and deploy advanced neural networks and machine learning (ML) for game rendering and streaming systems of SIE that exceed the state-of-the-art in runtime efficiency, visual quality and latency. What youll … least 1 research publication in a top-tier conference like CVPR, ECCV, ICCV, SIGGRAPH or similar Solid background in one or more of the following: (i) neural network architectures, evidenced (for example) by knowledge of how to formulate and test advanced loss functions in neural network design; (ii) design and test of advanced convolutional … recurrent, transformer-based, diffusion-based or other neural network architectures in a task-specific manner; (iii) some experience in training, validation and evaluation of deep neural network models on large datasets, evidenced by experience in using Python libraries like HDF5 or similar Desired qualifications: Publications, e.g. in top-tier conferences and journals: IEEE Transactions More ❯

Computing Group (VCG) and contribute to redefining the world of game play and live streaming via advanced R&D. VCG's mission is to design and deploy advanced neural networks and machine learning (ML) for game rendering and streaming systems of SIE that exceed the state-of-the-art in runtime efficiency, visual quality and latency. What you … least 1 research publication in a top-tier conference like CVPR, ECCV, ICCV, SIGGRAPH or similar Solid background in one or more of the following: (i) neural network architectures, evidenced (for example) by knowledge of how to formulate and test advanced loss functions in neural network design; (ii) design and test of advanced convolutional … recurrent, transformer-based, diffusion-based or other neural network architectures in a task-specific manner; (iii) some experience in training, validation and evaluation of deep neural network models on large datasets, evidenced by experience in using Python libraries like HDF5 or similar Desired qualifications: Publications, e.g. in top-tier conferences and journals: IEEE Transactions More ❯

including AI/Gen AI and machine learning. Experience analyzing large data sets, data cleaning, and statistical analysis. Proven experience with at least three machine learning algorithms (e.g., neural networks, logistic regression, random forests). Proficiency with Java and Python, understanding of data structures, algorithms, and software design patterns. Experience with AI/Gen AI frameworks like TensorFlow More ❯

looking for a motivated and skilled machine learning engineer to join our dynamic Brain & AI team. This role focuses on developing AI models that enhance our understanding of neural mechanisms building encoding and decoding models and apply this knowledge to real-world applications such as brain computer interfaces. You will be instrumental in pushing the boundaries of what … processing pipelines and devise effective solutions, improving performance and reliability. Maintain high standards of code quality, organization, and automatization across all projects. Adapt machine learning and neural network algorithms to optimize performance in various computing environments, including distributed clusters and GPUs. Write and revise papers, participate in conferences, communicate and disseminate results. Basic Qualifications: Degree in Computer … and fine-tuning generative models like diffusion models or large language models such as GPTs and LLAMAs. Experience with data and model visualization tools. Experience with non-invasive neural data (fMRI, EEG, MEG) or invasive neural recordings (ECoG, MEA, ecc). Important information for candidates Recruitment scams have become increasingly common. To protect yourself, please keep More ❯

systems Exposure/experience in containerization technologies like docker, Kubernetes, AWS EKS etc. Proficiency in ML algorithms, such as multi-class classification, decision trees, support vector machines, and neural networks (deep learning experience strongly preferred) Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g., AWS Bedrock, S3, SageMaker; Azure AI Search, OpenAI, blob storage, etc. More ❯

and common ML libraries such as TensorFlow, PyTorch, or similar. Experience with Jupyter Notebooks and version control (Git/GitHub). Basic understanding of supervised/unsupervised learning, neural networks, or clustering. Analytical Abilities Ability to interpret data trends, visualize outputs, and debug model behaviour. More ❯

design, including multivariate testing, regression/predictive modeling, causal inference, and A/B testing). Strong knowledge of various machine learning techniques (e.g., clustering, regression, decision trees, neural networks, etc.) and their real-world advantages and drawbacks. Proven experience applying statistical and modeling techniques to solve complex business problems in real-world scenarios. Proficiency in Python (for More ❯

leveraging Large Language Models, as well as a deep understanding of how to implement solutions using Retrieval Augmented Generation (RAG) architecture Experience with 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 biological ontologies Experience with complex More ❯

business. You will apply the appropriate solution to the problem at hand. This could be advanced statistical techniques (Hierarchical Bayesian modelling, GAMs), AI and machine learning techniques (LLMs, neural networks) or simple arithmetic. The key is to deliver useful and timely information for the benefit of Cox Automotive Europe and the broader automotive industry. We are seeking a More ❯

ideally working with data engineering. Proficiency in statistical analysis, machine learning, and data mining techniques. A good understanding of key machine learning models, including Gradient Boosting Machines (GBMs), Neural Networks and Large language models (LLMs). Hands-on experience with popular machine learning libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Knowledge of AWS products and More ❯

go-to expert in one or more technical areas. Design, implement and deliver performant and scalable algorithms based on state-of-the-art machine learning and neural network methodologies using distributed computing systems (CPUs, GPUs, TPUs, Cloud, etc.). Conduct rigorous data analysis and statistical modelling to explain and improve models. Report results clearly and efficiently, both More ❯

deliver our projects efficiently and effectively. The Data Scientist role combines data and analytics with applications knowledge. We make extensive use of advanced techniques including LLMs, Computer Vision; Neural Networks; NLP and advanced statistics. Education Qualification (Minimum) Bachelor's Degree in a STEM subject (typically, but not limited to: Maths; Physics; Physical/Engineering Sciences; Data Science; Computer More ❯

world problems; Expertise in one or more of the following: generative models, language models, computer vision, bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning; Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar; Experience with multi-GPU and distributed training at scale More ❯

data visualisation skills using tools like Tableau, Spotfire, Power BI etc. Expertise in predictive modelling, including both parametric (e.g. logit/probit) and non-parametric (e.g. random forest, neural net) techniques as well as wider ML techniques like clustering/random forest (desirable). Tech Stack: SQL, Python, R, Tableau, AWS Athena + More! More information: Enjoy fantastic More ❯

engineers, and business units to deliver value. Write high-quality Python code following best practices. Continuously research and apply new tools, techniques, and technologies. Experience with: Cloud deployment,Neural networks and libraries like TensorFlow, XGBoost, CatBoost, SKlearn, API development, SQL,CI/CD, DevOps, or MLOps pipelines Experience with: Strong hands-on experience or genuine interest in data More ❯

via APIs Familiarity with data visualization tools Knowledge of locating, assessing and integrating third party data-sets Experience with machine learning techniques and libraries (e.g., regression, classification, clustering, neural networks). Solid understanding of AI concepts, including supervised and unsupervised learning. Knowledge of cloud computing platforms (e.g., AWS, GCP, Azure) Education and Knowledge Bachelor's or Master's More ❯

Architecture & Hands-On Development Define and implement end-to-end AI pipelines: data collection/cleaning, feature engineering, model training, validation, and inference. Rapidly prototype novel models (e.g., neural networks, probabilistic models) using PyTorch, TensorFlow, JAX, or equivalent. Productionize models in cloud/on-prem environments (AWS/GCP/Azure) with containerization (Docker/Kubernetes) and ensure … record of shipping AI/ML products end-to-end (from prototype to production). Hands-on expertise building and deploying deep learning models (e.g., CNNs, Transformers, graph neural networks) in real-world applications. Proficiency in Python and core ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face, etc.). Strong software engineering background: data structures, algorithms, distributed systems More ❯

the time and complexity of application validation and delivery. This role requires someone who can see beyond traditional automation approaches, bringing fresh perspectives on how to leverage LLMs, neural networks, and emerging AI technologies to solve complex application testing and deployment challenges. Key job responsibilities Design AI-powered test automation frameworks that leverage machine learning for intelligent test More ❯

Other services require a good working knowledge of Databricks, Logic Apps, and the Power Platform knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc) and their real-world advantages/drawbacks knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc) experience with the More ❯

Generation (RAG) methods Solve industry relevant problems Design and implement artificial intelligence systems and applications that can simulate human intelligence processes through the creation and validation of algorithms, neural networks, and other machine learning techniques. Collaborate with cross-functional teams to ensure seamless integration of software components. Stay updated with the latest trends and advancements in the Technology More ❯

and a growth mindset. What You’ll Do Design, build, and scale machine learning models using environmental and observational data. Apply advanced causal inference techniques such as Bayesian Neural Networks, Gaussian Processes, Difference-in-Differences, and Synthetic Control methods. Leverage foundation models (e.g. Prithvi, Clay) and transformers to extract insights from complex datasets. Work cross-functionally with science More ❯

e.g., Python, Java, C#). 2+ years of experience in the production deployment of Automation Anywhere A360 bots. Knowledge and understanding of Generative AI techniques, including deep learning, neural networks, and natural language processing. Familiarity with process analysis and improvement methodologies. Excellent problem-solving skills and attention to detail. Ability to work collaboratively in a team environment and More ❯

grow Experience Implementing machine learning in production using in-house or third-party data science platforms Building machine learning models; experience in Natural Language Processing, Time-Series prediction, Neural Networks and Recommendation Systems will be advantageous. You possess excellent communication skills, explaining complicated concepts to non-technical colleagues. Generating insights from complex data sources. More ❯

these areas is essential. Essential Skills: .NET C# Mvc (Framewrk and/or Core) WebApi SignalR Python programming experience Previous experience in the development and use of Convolution Neural Networks (CNN s) for machine vision and image analysis applications Experience with large-scale data sets Experience with open source machine learning platforms such as Keras/tensorflow or More ❯