1 to 25 of 48 Neural Network Jobs

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 »

consultative approach to distil complex requirements into robust data science models such as regression and propensity models, time-series modelling, ensemble methods, or neural networks for optimal decision-making. Spearhead initiatives with cross-functional stakeholders. ● Opportunity Identification: Partner with business stakeholders to unearth untapped data science applications utilising more »

consultative approach to distil complex requirements into robust data science models such as regression and propensity models, time-series modelling, ensemble methods, or neural networks for optimal decision-making. Spearhead initiatives with cross-functional stakeholders. ● Opportunity Identification: Partner with business stakeholders to unearth untapped data science applications utilising more »

consultative approach to distil complex requirements into robust data science models such as regression and propensity models, time-series modelling, ensemble methods, or neural networks for optimal decision-making. Spearhead initiatives with cross-functional stakeholders. ● Opportunity Identification: Partner with business stakeholders to unearth untapped data science applications utilising more »

Machine Learning Engineer Edinburgh (remote) £50,000-£65,000 About the Company: Our client is a visionary network intelligence company at the forefront of developing a cutting-edge deep traffic analysis platform for mobile network operators. Their innovative solutions help reduce operational costs, optimize energy consumption, and enhance … enthusiastic Machine Learning Engineer to join our team and work on designing, training, testing, and integrating industry-grade machine learning models for deep mobile network traffic analysis. You will expand our portfolio of neural network architectures for traffic forecasting, anomaly prediction, and decomposition, collaborating with other … and debug code in Python, utilizing deep learning frameworks like TensorFlow 2 and Keras Perform in-depth data analysis tasks and design new neural architectures Participate in code reviews, maintain codebase quality, and ensure feature sustainability Investigate problems and devise solutions for large data sets Prototype implementations of more »

cluster computing and containerization Experience working in parallel/scalable languages such as Spark or Dask Experience working with knowledge graphs and graph neural networks Biotech or biopharma experience, ideally within R&D Experience in a startup or scale-up environment Dewpoint Therapeutics is the first company founded 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: Join a pioneering joint venture at the intersection of AI 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 »

with data manipulation and analysis libraries (e.g., Pandas, NumPy, SciPy). Strong knowledge of machine learning techniques and algorithms (e.g., regression, classification, clustering, neural networks). Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau) and proficiency in SQL for data extraction and manipulation. Excellent problem-solving skills 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 »

or Java, as well as familiarity with machine learning frameworks such as TensorFlow or PyTorch. Strong understanding of AI concepts and techniques, including neural networks, deep learning, and reinforcement learning. Experience with cloud computing platforms such as Azure, AWS, or Google Cloud, and familiarity with containerization technologies such 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 »

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 »

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 »

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 »

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 »

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

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 »

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 »

on a daily basis to help our customers detect financial crime and other risks will include: Entity Resolution, Natural Language Processing (NLP) techniques, Neural Networks, Large Language Models and Visual Analytics. You will therefore need to be able to pick up new ideas and concepts quickly and be more »

whilst supporting our employees. We are currently looking for a researcher in our Computing Research Group, working on exploring how the use Graph Neural Networks for healthcare related applications. We have a strong preference for the development of AI techniques that can be applied in the real … world and that directly contribute to social good. Your role will involve: The development of new state-of-the-art Graph Neural Network techniques to be applied to large scale data coming from healthcare applications Implementation of these techniques into proof-of-concept code and demonstrations that more »