1 to 25 of 93 Neural Network Jobs in the UK

AI Compiler Engineer - Compilation - TVM - MLIR - Deep Learning - Neural network Compiler - Remote Our client is seeking a Staff AI Compiler Engineer to lead the design and evolution of their cutting-edge neural network compiler. This is a key technical leadership role focused on architecting scalable, high-performance software solutions that power next-generation AI … hardware. Key Responsibilities Lead the architecture, design, and hands-on development of the neural network compiler and SDK. Develop advanced compiler optimizations tailored to in-memory computing architectures, with a focus on hardware-aware transformations. Drive complex, long-term initiatives to expand compiler support to emerging workloads (eg, generative AI) and future versions of the client's … runtime integration Solid understanding of computer architecture and heterogeneous compute systems. Hands-on experience with open-source compiler frameworks (eg, TVM, MLIR, Glow). Familiarity with neural network quantization techniques is a strong plus. Proficiency with PyTorch and a solid grasp of modern deep learning frameworks. Strong coding skills in both C++ and Python 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 ❯

centers in Cambridge, London, Edinburgh and Ipswich. We continue to explore and define new research directions and new services. We have expanded our collaborations with academic researchers; researched new network architectures, integration of communications and key enabling technologies; and developed the fundamental theories of these technologies. We invite you to join us on this exciting journey and drive your … This is not a maintenance role; it is a ground-zero opportunity to architect the low-level software stack for a heterogeneous computing platform where the GPU, NPU (Neural Processing Unit) and other modules are designed for deep, synergistic cooperation. Your work will be critical to unlocking the full potential of neural rendering, machine learning and … AI workloads. Performance Analysis & Optimization: Attain unparalleled performance by deep-diving into the hardware pipeline. Identify and eliminate bottlenecks in the interaction between graphics shaders and neural network execution. Define the Programming Model: Create and document the programming models, APIs, and developer tools that will allow internal and external graphics engineers to leverage the combined power of More ❯

data Translate complex business needs into thoughtful, practical data products that support better decision-making Apply a wide toolkit of methods from classical statistics and regression models to neural networks, ensemble methods, and AI techniques, to answer important business questions Share insights through clear, compelling storytelling, dashboards, and visualisations that empower senior stakeholders to act with confidence Coach More ❯

and work collaboratively in a team environment Nice to Have (But Not Required): Experience from a university project, hackathon, or internship involving AI or machine learning Understanding of neural networks, NLP, or computer vision concepts Experience using Jupyter notebooks, Git, or cloud platforms (AWS, GCP, Azure) Knowledge of SQL or data wrangling techniques What You’ll Gain Real More ❯

and work collaboratively in a team environment Nice to Have (But Not Required): Experience from a university project, hackathon, or internship involving AI or machine learning Understanding of neural networks, NLP, or computer vision concepts Experience using Jupyter notebooks, Git, or cloud platforms (AWS, GCP, Azure) Knowledge of SQL or data wrangling techniques What You’ll Gain Real More ❯

and work collaboratively in a team environment Nice to Have (But Not Required): Experience from a university project, hackathon, or internship involving AI or machine learning Understanding of neural networks, NLP, or computer vision concepts Experience using Jupyter notebooks, Git, or cloud platforms (AWS, GCP, Azure) Knowledge of SQL or data wrangling techniques What You’ll Gain Real More ❯

and work collaboratively in a team environment Nice to Have (But Not Required): Experience from a university project, hackathon, or internship involving AI or machine learning Understanding of neural networks, NLP, or computer vision concepts Experience using Jupyter notebooks, Git, or cloud platforms (AWS, GCP, Azure) Knowledge of SQL or data wrangling techniques What You’ll Gain Real More ❯

and work collaboratively in a team environment Nice to Have (But Not Required): Experience from a university project, hackathon, or internship involving AI or machine learning Understanding of neural networks, NLP, or computer vision concepts Experience using Jupyter notebooks, Git, or cloud platforms (AWS, GCP, Azure) Knowledge of SQL or data wrangling techniques What You’ll Gain Real More ❯

and work collaboratively in a team environment Nice to Have (But Not Required): Experience from a university project, hackathon, or internship involving AI or machine learning Understanding of neural networks, NLP, or computer vision concepts Experience using Jupyter notebooks, Git, or cloud platforms (AWS, GCP, Azure) Knowledge of SQL or data wrangling techniques What You’ll Gain Real More ❯

with engineering and data teams to ensure scalable solutions Requirements Extensive experience in data science, including applied statistics and machine learning Familiarity with supervised and unsupervised learning, NLP, neural networks, Bayesian statistics, time-series forecasting, collaborative filtering, and deep learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Experience with cloud platforms More ❯

Translating complex business needs into thoughtful, practical data products that support fairer and more innovative pricing approaches Applying a wide toolkit of methods - from time-series modelling to neural networks - to answer important business questions Sharing insights in clear, compelling ways that empower senior decision-makers to act confidently Coaching and encouraging junior data scientists, creating space for More ❯

linear algebra and calculus Collaborative, humble and enthusiastic attitude Preferred qualifications, capabilities and skills Experience deploying on AWS cloud infrastructure using Lambda, Glue, S3 etc Experience in deep neural networks and familiarity with the latest developments in related fields Experience in LLM model finetuning and continuous learning techniques Experience in prompt engineering techniques and state-of-the-art More ❯

where their work genuinely moves the 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 Computing, AWS, Azure, Google More ❯

in both on-prem and cloud environments (e.g., Azure, AWS, GCP). Strong knowledge of machine learning and statistical modeling techniques, including regression, time-series forecasting, boosted trees, neural networks, and reinforcement learning. Familiarity with optimization and simulation methods such as mixed-integer programming, heuristics, or Monte Carlo simulation. Proven ability to translate analytical findings into operational actions More ❯

pipelines (realtime or batch) & data quality using modern toolchain (e.g., Apache Spark, Kafka, Airflow, dbt). Strong foundational knowledge of machine learning and deep learning algorithms, including deep neural networks, supervised/unsupervised learning, predictive analysis, and forecasting. Expert-level proficiency in Python, with a demonstrated ability to develop and debug production-grade code. Desired Skills (Bonus Points More ❯

pipelines (realtime or batch) & data quality using modern toolchain (e.g., Apache Spark, Kafka, Airflow, dbt). Strong foundational knowledge of machine learning and deep learning algorithms, including deep neural networks, supervised/unsupervised learning, predictive analysis, and forecasting. Expert-level proficiency in Python, with a demonstrated ability to develop and debug production-grade code. Desired Skills (Bonus Points More ❯

pipelines (realtime or batch) & data quality using modern toolchain (e.g., Apache Spark, Kafka, Airflow, dbt). Strong foundational knowledge of machine learning and deep learning algorithms, including deep neural networks, supervised/unsupervised learning, predictive analysis, and forecasting. Expert-level proficiency in Python, with a demonstrated ability to develop and debug production-grade code. Desired Skills (Bonus Points More ❯

pipelines (realtime or batch) & data quality using modern toolchain (e.g., Apache Spark, Kafka, Airflow, dbt). Strong foundational knowledge of machine learning and deep learning algorithms, including deep neural networks, supervised/unsupervised learning, predictive analysis, and forecasting. Expert-level proficiency in Python, with a demonstrated ability to develop and debug production-grade code. Desired Skills (Bonus Points More ❯

pipelines (realtime or batch) & data quality using modern toolchain (e.g., Apache Spark, Kafka, Airflow, dbt). Strong foundational knowledge of machine learning and deep learning algorithms, including deep neural networks, supervised/unsupervised learning, predictive analysis, and forecasting. Expert-level proficiency in Python, with a demonstrated ability to develop and debug production-grade code. Desired Skills (Bonus Points More ❯

e.g., NumPy, pandas, scikit-learn, 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 policies, load balancers, Public Key More ❯

e.g., NumPy, pandas, scikit-learn, 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 policies, load balancers, Public Key More ❯

e.g., NumPy, pandas, scikit-learn, 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 policies, load balancers, Public Key More ❯

e.g., NumPy, pandas, scikit-learn, 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 policies, load balancers, Public Key More ❯

e.g., NumPy, pandas, scikit-learn, 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 policies, load balancers, Public Key More ❯