26 to 50 of 66 Neural Network Jobs in London

You will be building upon cutting-edge ML techniques such as transformers and reinforcement learning to create novel multi-modal solutions. Examples include sensor fusion systems, physics-informed neural networks for simulations, and multi-purpose autonomous robots. Projects will be defence focused but may include offensive capabilities. **Please note, as projects are defence related, you will need to More ❯

equivalent experience in a relevant discipline e.g. engineering, mathematics, physics, statistics Experience of data science in finance, insurance or Ecommerce is an advantage but not required. Experience with neural networks and Tensor Flow, CatBoost, XGBoost, SKlearn, Pandas If you hold the experience and technical skills outlined above which would enable you to hit the ground running, please apply More ❯

descent), and fixed-memory data structures (e.g. Bloom Filters). • Experience using next generation machine learning techniques and tools, including Deep Neural Networks and TensorFlow. • Exposure to Network Theory, especially social network analysis and graph diffusion analysis. Ability to build custom data visualisations, prototype browser based UX/UI, and the server side microservices to support More ❯

Computer Science, Machine Learning, or a closely related field Strong foundation in machine learning and deep learning algorithms (e.g., transformers, GNNs, supervised/unsupervised learning, reinforcement learning, deep neural networks) Excellent Python programming skills with experience in developing and debugging production-level code Desired Skills (Bonus Points): Proven experience in recommender systems, behavioural AI, and/or reinforcement More ❯

Computer Science, Machine Learning, or a closely related field Strong foundation in machine learning and deep learning algorithms (e.g., transformers, GNNs, supervised/unsupervised learning, reinforcement learning, deep neural networks) Excellent Python programming skills with experience in developing and debugging production-level code Desired Skills (Bonus Points): Proven experience in recommender systems, behavioural AI, and/or reinforcement More ❯

Who You Are You have a strong background in machine learning, enjoy applying theory to develop real-world applications, with experience and expertise in bandit algorithms, LLMs, general neural networks, and/or other methods relevant to recommendation systems. You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages. More ❯

Woven by Toyota, we are at the forefront of developing advanced Machine Learning solutions for autonomous driving. Our team tackles groundbreaking challenges in designing state-of-the-art neural networks, pioneering innovative end-to-end architectures, and advancing ML techniques in perception, prediction, and motion planning. We're passionate about pushing the boundaries of autonomous systems through deep More ❯

preparation, exploratory analysis, model training, validation, and deployment. Develop and fine-tune predictive algorithms such as: Classification: Logistic Regression, Decision Trees, Random Forests. Regression: Linear Models, Gradient Boosting, Neural Networks, K-Nearest Neighbors. Build models for customer behavior prediction and risk assessment in insurance, particularly in underwriting and claims. Apply natural language processing (NLP) for tasks like document More ❯

preparation, exploratory analysis, model training, validation, and deployment. Develop and fine-tune predictive algorithms such as: Classification: Logistic Regression, Decision Trees, Random Forests. Regression: Linear Models, Gradient Boosting, Neural Networks, K-Nearest Neighbors. Build models for customer behavior prediction and risk assessment in insurance, particularly in underwriting and claims. Apply natural language processing (NLP) for tasks like document More ❯

preparation, exploratory analysis, model training, validation, and deployment. Develop and fine-tune predictive algorithms such as: Classification: Logistic Regression, Decision Trees, Random Forests. Regression: Linear Models, Gradient Boosting, Neural Networks, K-Nearest Neighbors. Build models for customer behavior prediction and risk assessment in insurance, particularly in underwriting and claims. Apply natural language processing (NLP) for tasks like document More ❯

Master's degree in Computer Science, Cybersecurity, AI, or related field. 8+ years of experience in cybersecurity, with expertise in AI security . Deep understanding of machine learning, neural networks, and adversarial attacks . Proficiency in cryptographic techniques and secure AI model development . Strong experience with penetration testing, threat intelligence, and security auditing . Familiarity with frameworks More ❯

thinking in reasoning and planning. Lead applied research projects end-to-end: from ideation and literature review to prototyping and deployment. Write high-quality, robust code that integrates neural and symbolic components. Collaborate with a team of scientists and engineers, articulating complex ideas clearly to technical and non-technical audiences. Analyse and inspect large-scale datasets to support … neural training and symbolic extraction. What We're Looking For: Deep learning expertise with significant industry experience, and c. 2+ years applying it to language generation, including working with Large Language Models, neurosymbolic integration and knowledge representation. Experience with Python and common ML Frameworks like Pytorch, HF Transformers, Tensorflow, JAX. Track record working as an independent contributor capable … engineers, and non-technical stakeholders. Desirable: Use of Python libraries that encourage best practices such as pytest, pylint, black etc. Experience with symbolic reasoning engines and integration with neural networks. Strong technical writing skills as evidenced by relevant publications or blogs. Start-up experience. Git/Github Proficiency working with cloud platforms for deploying hybrid AI systems. Please More ❯

Previous experience within Personal Lines Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science, Actuarial Science More ❯

Previous experience within Personal Lines Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science, Actuarial Science More ❯

feature engineering, build training pipelines, and achieve acceptable performance. At Kumo, we are building a machine learning platform for data lakehouses, enabling data scientists to train powerful Graph Neural Net models directly on their relational data, with only a few lines of declarative syntax known as Predictive Query Language. The Kumo platform enables users to build models a More ❯

finale of the fellowship is Demo Day. Fellows have the opportunity to present their hard work to an audience of 100+ guests. The event is a great chance to network with hiring managers and influential individuals from a wide range of businesses from London, the UK and Europe. After completing the Faculty Fellowship, our alumni have gone on to … The ability to code or have programming experience, especially in Python. Some experience with theoretical concepts of statistical learning (e.g. hypothesis testing, Bayesian Inference, Regression, SVM, Random Forests, Neural Networks, Natural Language Processing, optimisation). Experience with some coding libraries frequently used in data science. The ability to communicate effectively. Experience composing and following a project plan/… where all the fellowship alumni discuss data science news, techniques, conferences and much more. Faculty provides career support to the graduated fellows - once you are part of our "professional network", we will be delighted to keep in touch and help you succeed in your data science career. What we can offer you: The Faculty team is diverse and distinctive More ❯

Join us at the heart of the Kumo Graph Neural Network and Relational Deep Learning architecture, where you'll play a pivotal role in shaping and expanding its capabilities. You'll drive innovative designs that enhance our GNN backbone and integrate cutting-edge temporal learning strategies. Your work will bridge the gap between foundational models and GNNs More ❯

multi-disciplinary team, with diverse trading strategies across spot FX, NDFs, and swaps. The ideal people for these roles have eFX modelling experience and practical experience with applying neural nets to time series modelling. People who lack eFX experience, but have several years of real-world experience applying neural nets to time series in any industry More ❯

list of benefits, speak to our recruitment team. We are looking for: We are particularly interested in candidates with experience in ONE of the following: Neuromorphic Computing, Spiking Neural Networks and event-based event monitoring/sparse data. Or: Advanced statistics and experience operationalising academic research Security clearance: You must be able to gain and maintain the relevant More ❯

thinking in reasoning and planning. Lead applied research projects end-to-end: from ideation and literature review to prototyping and deployment. Write high-quality, robust code that integrates neural and symbolic components. Collaborate with a team of scientists and engineers, articulating complex ideas clearly to technical and non-technical audiences. Analyse and inspect large-scale datasets to support … neural training and symbolic extraction. What We're Looking For: Deep learning expertise with significant industry experience, and c. 2+ years applying it to language generation, including working with Large Language Models, neurosymbolic integration and knowledge representation. Demonstrable experience leading in an individual contributor capacity-setting technical direction, influencing others, and delivering high-impact work without direct management … engineers, and non-technical stakeholders. Desirable: Use of Python libraries that encourage best practices such as pytest, pylint, black etc. Experience with symbolic reasoning engines and integration with neural networks. Strong technical writing skills as evidenced by relevant publications or blogs. Start-up experience. Git/Github Proficiency working with cloud platforms for deploying hybrid AI systems. Please More ❯

implementation and operational expertise. 2+ years directly running a technology pre-sales engineering organization and leading cross functional teams. Domain knowledge of service assurance, performance monitoring, routing, optical, optics, network automation, automation tools, SDN, ROADM, DWDM, metro core, access, edge, and aggregation network. Strong awareness and understanding of TWAMP, RON, SDN, SRv6, BNG, MPLS-SR, VxLAN, EVPN and ECMP. … as well as technical messaging with marketing as the voice of the customer. Strong understanding of AI/ML concepts, techniques & infrastructure (learning models, LLM, GenAI, AGI, NLP, neural networks, deep learning, AI Frameworks, GPU and DPU). Strong knowledge of customer networks, their current challenges, ability to act as consultant and guide the customers - particularly Service Providers More ❯

Mathematics, Physics, Statistics, or Engineering. Demonstrated experience developing systematic cash equity/statistical arbitrage strategies. Experience with machine learning models and/or statistical learning models (e.g. LLMs, neural networks, Deep Learning models, etc.). Capacity to excel in a fast-paced environment. Strong coding skills in at least one of the following programming languages: Python, R, MATLAB More ❯

Mathematics, Physics, Statistics, or Engineering. Demonstrated experience developing systematic cash equity/statistical arbitrage strategies. Experience with machine learning models and/or statistical learning models (e.g. LLMs, neural networks, Deep Learning models, etc.). Capacity to excel in a fast-paced environment. Strong coding skills in at least one of the following programming languages: Python, R, MATLAB More ❯

experience. Key Responsibilities: Develop and maintain PyTorch integration for a custom AI platform. Build and optimize kernels and libraries for core AI operations. Create tooling for neural network deployment and optimization. Benchmark, analyze, and improve AI workload performance. Collaborate with the hardware team to guide architectural decisions. Extend support to additional frameworks (e.g., TensorFlow, ONNX). Produce More ❯

software Experience in SOME of the following predictive modelling techniques e.g.Logistic Regression, Log-Gamma GLMs, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Support Vector Machines and Neural Nets Experienced in the use of a programming language (e.g. R, Matlab, Python or Octave) Experience of using Emblem and Radar Highly numerate with excellent attention to detail Ability More ❯