1 to 25 of 39 Permanent Neural Network Jobs in the UK

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 »

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 »

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 »

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 »

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 »

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 »

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 »

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 »

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 »

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 »

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 »

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 »

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 »

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 »

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) Data Wrangling Systems: Linux, APIs, infrastructure design load balancing, VMs, PostgreSQL, vector dbs. ML Learning Engineer desirable skills: Version more »

knowledge graphs (KG) by reasoning over and inferencing from existing KG data using graph data science (GDS), graph machine learning (GML), and Graph Neural Networks (GNNs) approaches. Benefits and Perks: An engaging remote-first culture A great compensation package that includes BenchSci equity options A robust vacation policy 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 »

Possess a strong foundational knowledge of AI, ML, and data science principles, including signal/pattern recognition, classification techniques, and deep neural network training. Have practical experience with various Data Science and ML frameworks or tools. Excellent verbal and written communication skills Proficient in using MS Office more »

management skills, with a proven track record of delivering projects on time and within scope. fundamentals in programming, statistics, mathematics, and ML algorithms (neural networks, tree-based methods, optimizers, super/unsupervised learning, feature engineering, etc.). Strong experience with Python required understanding of the ML/DS more »

you: Proficiency in Python Strong NLP experience – NumPy, Pandas Commercial hands-on experience with Hugging Face and finetuning LLMs Expertise in learning algorithms, neural networks and ML frameworks (TensorFlow, PyTorch) Nice to have: Familiarity with Git or other Version Control Systems Computer Vision Library exposure Understanding of Big more »