18 of 18 Neural Network Jobs in the South East

D projects to drive step changes in the Stack’s capabilities longer term. The code frameworks you will work on include neural network execution engines, genetic algorithms and training frameworks. This dynamic role will require you to have a broad interest in and experience in software engineering … working collaboratively with other developers on innovative code bases.Experience of genetic algorithms, low level neural network execution and concepts such as neuroplasticity, recurrent neural networks and reinforcement learning frameworks like OpenAI Gym would be a huge advantage. This role requires specific experience with Python and … discipline Strong experience with a statically typed language, preferably C, C++, or Rust Experience with genetic algorithms or neuroevolution Experience with neural network concepts such as neuroplasticity and recurrent neural networks Experience of reinforcement learning frameworks like OpenAI Gym Experience with software optimisation or high More ❯

D projects to drive step changes in the Stack’s capabilities longer term. The code frameworks you will work on include neural network execution engines, genetic algorithms and training frameworks. This dynamic role will require you to have a broad interest in and experience in software engineering … working collaboratively with other developers on innovative code bases.Experience of genetic algorithms, low level neural network execution and concepts such as neuroplasticity, recurrent neural networks and reinforcement learning frameworks like OpenAI Gym would be a huge advantage. This role requires specific experience with Python and … discipline Strong experience with a statically typed language, preferably C, C++, or Rust Experience with genetic algorithms or neuroevolution Experience with neural network concepts such as neuroplasticity and recurrent neural networks Experience of reinforcement learning frameworks like OpenAI Gym Experience with software optimisation or high More ❯

/ML Engineers 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 … trends. Skills and Qualifications: Minimum 4 years of experience in building AI/ML software. Strong expertise in machine learning and neural network algorithms. Proficient in programming languages like Python, and libraries such as TensorFlow, PyTorch, NumPy and LangChain Experience with server deployment, cloud computing environments, and More ❯

flexibility, and efficiency to handle large algorithms. Algorithm Development: Develop and implement advanced AI algorithms and models, including machine learning, deep learning, and neural networks. Continuously evaluate and improve these algorithms to enhance system performance and accuracy. Data Integration: Identify relevant data sources and design methods for data … Implement evaluation methodologies to measure the performance and effectiveness of trained models. Fine-tune models based on feedback and data insights. Neural Network Design: Design and optimize deep learning neural networks for various AI tasks, such as natural language processing, computer vision, recommendation systems, and … field. Experience with large language models (LLMs) and prompt engineering. Experience in designing and developing AI systems, including machine learning, deep learning, and neural networks. Strong programming skills in languages such as Python, R, or Java Familiarity with AI libraries, frameworks, and tools such as TensorFlow, PyTorch, or More ❯

Data Science, Computer Science, Mathematics, or a related field. Experience or coursework in machine learning, deep learning, or AI techniques (e.g., supervised learning, neural networks, NLP). Proficiency in Python and libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers. Familiarity with data preprocessing, model evaluation, and More ❯

Computer Science, Machine Learning, or a closely related field. Machine learning expertise : Strong foundation in machine learning and deep learning algorithms (e.g., deep neural networks, supervised/unsupervised learning, predictive analysis, forecast modelling). Programming proficiency: Excellent Python programming skills with experience in developing and debugging production-level More ❯

other container languages A passion for applying tech to solve healthcare challenges. Non-essential skills/nice to have: Experience or understanding of Neural Networks Experience with Biotechnology/Bioinformatics Familiarity with AWS, Kubernetes, or RESTful APIs. Exposure to regulated medical software environments. If you are interested, please More ❯

Python and potentially R. Expertise with relevant ML frameworks (e.g., scikit-learn, PyTorch). Experience with recommendation systems, collaborative filtering, and ideally Graph Neural Networks (GNNs). Proficient with SQL and working with large datasets (e.g., GCP BigQuery). Experience with cloud platforms (specifically GCP) and CI/… skills and ability to quickly adapt to new model types and requirements. Strong communication and stakeholder management skills. Expertise in advanced neural network architectures (Autoencoders, Transformers). Ability to rapidly acquire complex domain knowledge. More ❯

a deep-tech start-up looking for an experienced AI Engineer to join their expanding team. This role focuses on developing Neural Network-based NLP and Computer Vision algorithms, working alongside institutional, academic, and commercial partners. The Role • Develop/refine AI models for NLP • Design new … Clearance (or eligible for SC Clearance) • MSc/PhD in CS, Engineering, Maths or relevant field (or equivalent experience) • Expertise in Neural Network-based NLP & LLM • Strong Python skills • Collaborative, analytical, and problem-solving mindset Gen AI Engineer – Hybrid (Oxford 2 Days/Week) – £100,000+ – SC More ❯

one hand, Bayesian learning provides a theoretically sound framework to formalise the estimation of the architecture and the parameters of deep neural network models. On the other hand, deep learning offers new tools in Bayesian modelling, e.g. to learn flexible nonparametric priors or computationally efficient posterior distribution … approximations. State of the Art The field of machine learning has recently been much impacted by deep learning. Deep neural networks are now at the basis of the state-of-the-art in computer vision, natural language processing, to cite just a few. While very effective, these models … uncertainty, and it is one of the cornerstones of modern machine learning. At the same time, the theory at the basis of deep neural networks is not yet very well understood and its grounds must be laid out. Although the interaction between these two learning paradigms is relatively More ❯

privacy services. Databricks and PySpark Analysing blockchain data Building and maintaining data pipelines Deploying machine learning models Use of graph analytics and graph neural networks If this sounds like you then please do reach out and let's have a chat More ❯

great technical understanding of various machine learning approaches, which would include regression methods, probabilistic pricing models, tree based gradient boosting approaches, information theory, neural networks, transfer learning, etc. While your focus will be primarily on the Valuations and Pricing Team you'll also work alongside your peers in More ❯

applied to financial markets, time-series analysis, or similar data-intensive domains. Deep theoretical knowledge of machine learning, with expertise in areas such neural networks and statistical modelling. Advanced programming proficiency in Python or C# , with a track record of writing production-ready code. Demonstrated ability to articulate More ❯

experience applying AI in a commercial or customer-focused environment. Hands-on knowledge in areas such as signal processing, reinforcement learning, neural network training, or multi-agent systems. Familiarity with research publishing processes and participation in academic or industry conferences. Responsibilities Leading research initiatives that explore the More ❯

experience applying AI in a commercial or customer-focused environment. Hands-on knowledge in areas such as signal processing, reinforcement learning, neural network training, or multi-agent systems. Familiarity with research publishing processes and participation in academic or industry conferences. Responsibilities Leading research initiatives that explore the More ❯

new and exciting ways. If you’re looking for a challenging career working in a vibrant environment with access to training and a global network of experts, this could be the role for you. As part of our global team, you'll be working with cutting-edge technologies and … Text, PDFs, jpgs, call recordings, video, etc. Knowledge of machine learning modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the More ❯

a unique opportunity to develop and deploy advanced AI models in high-impact environments. 🚀 What You'll Be Doing Designing, developing, and training neural networks to meet complex functional requirements. Deploying AI models efficiently on scalable server-based platforms. Collaborating with cross-functional teams to integrate ML capabilities … Continuously improving model performance and infrastructure through experimentation and optimisation. 🧠 What We're Looking For Strong understanding of AI/ML fundamentals, including neural networks and deep learning architectures. Proficiency in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Experience deploying machine learning models More ❯

The Company Luffy AI is an exciting high-tech startup developing adaptive neural networks for industrial control & robotics. Luffy specialises in “Micro AI” controllers that can be trained in simulation on digital twins and successfully transferred into real world systems. The Micro AI controllers can be deployed on … existing controller hardware with a small footprint and no internet connection. Our networks use neural plasticity to learn the dynamics of the equipment they are placed in and continue to adapt long after training. These innovations allow us to overcome the difficulty of applying AI in control system More ❯