26 to 39 of 39 Deep Learning Jobs in London

initiatives. This is a high-impact, hybrid role designed for a technical visionary who can bridge the gap between cutting-edge machine learning and commercial product delivery. You will be responsible for leading the technical direction, building end-to-end AI products, and managing a team of data scientists … strategic partner to the business. Required Qualifications ML Mastery: Proven track record in Data Science/ML with expertise in Python, SQL, and deep learning libraries (TensorFlow, Keras, or PyTorch). Production Experience: Demonstrated experience deploying real-world AI solutions at scale; purely academic or research backgrounds will ...

actively expanding into new application areas such as aerospace, immersive technologies, and assistive systems. The Role You will work at the intersection of machine learning, computer vision, and cognitive science to build models that predict and interpret human attention and behaviour in visual and spatial contexts. Key responsibilities include … Designing and implementing machine learning models for human attention, perception, and interaction.Running independent experiments, from hypothesis and data design through to evaluation and analysis.Working with visual, temporal, and spatial data including images, video, 3D scenes, and gaze signals.Translating research ideas into practical prototypes with support from a small engineering ...

preprocessing to ensure high-quality inputs for ML models. Model Development: Select and train appropriate architectures (BERT, GPT, etc.) using supervised, unsupervised, or reinforcement learning strategies. Prompt Engineering: Design, test, and iterate on complex prompts to elicit high-quality responses from LLMs while mitigating unintended behaviors. Evaluation & Optimization: Define … establish automated monitoring systems to track drift and performance. Technical Requirements Core AI/ML: Strong experience in ML algorithms, LLM architectures, and deep learning frameworks. Generative AI: Proven expertise in Prompt Engineering and fine-tuning pre-trained models. Engineering: Proficiency in Python and experience designing data pipelines ...

Fraud Operations Director in Fintech, you will work in a highly collaborative environment with extensive amounts of data to research and develop deep learning models to solve real-world problems and apply them to tasks such as identifying bad actors, preventing fraud, building anomaly detection models, and analytics … shared goals. Successful outcomes in this role will significantly impact the business. Responsibilities: Lead the development and optimization of fraud detection systems using machine learning and rule-based engines. Work closely with management, product, engineering, compliance, legal, and security teams to align, present, and implement end-to-end fraud ...

monitor models in production — performance, availability, relevance → Lead A/B testing and offline experiments to drive continuous improvement → Evaluate emerging research in deep learning and GenAI for real-world integration What we're looking for: ✦ Full ML lifecycle experience — from development through to monitoring in prod ✦ Python ...

Working closely with the founders, you will influence both the technical roadmap and future diversification into new application areas. Key responsibilities include: Developing machine learning and computer vision models focused on human attention, perception, and intent Designing and running experiments independently across visual and spatial data Working with multimodal … academic venues while working on applied problems Your Skills and Experience PhD or near completed PhD, or equivalent research experience, in computer vision, machine learning, neuroscience, cognitive science, robotics, HCI, or a related field Strong publication record, ideally at venues such as CVPR or ICCV, or equivalent research output ...

Expert – Expert in building and evaluating Generative AI solutions and Large Language Models (LLMs) for various use cases. Experience in developing and implementing machine learning models, including predictive, forecasting, classification, and deep learning models. CX Data Experience - Hands-on experience in customer behaviour analytics, marketing, commercial … oral presentation skills, that engages internal and external audiences Innovative Mind - A strong interest and experience with the latest advancements in data, AI, machine learning, and data science space If this sounds like you, please do get in touch for a confidential discussion to find out more. ...

teams building real-world AI products as well as advancing core model research. We are looking for candidates with: A PhD in AI, machine learning, robotics, computer science, or a related technical field Research or engineering experience in vision, audio, language, robotics, multimodal systems, or deep learning … expertise Interest in joining high-growth startup environments Ability to move between research, experimentation, and production impact Typical roles include: AI Research Scientist Machine Learning Engineer Applied AI Engineer Computer Vision Researcher Speech/Audio AI Researcher NLP/LLM Researcher Robotics Researcher/Engineer Multimodal AI Scientist ...

Looker,... Background in Data Governance and Data Catalog solutions: Axon, Informatica EDC, Colibra, Purview, etc. Previous experience in Artificial Intelligence techniques: ML/Deep Learning, Computer Vision, NLP, etc General information: Start Date: ASAP Length of Contract: 1 year (minimum) Work Location: Madrid Remote working. ...

time in understanding the architecture and domain before making changes to the most critical components. Were looking for someone who enjoys that kind of deep learning and is keen to build long-term expertise that enables them to take on greater ownership and impact. Good team player Autonomous ...

time in understanding the architecture and domain before making changes to the most critical components. Were looking for someone who enjoys that kind of deep learning and is keen to build long-term expertise that enables them to take on greater ownership and impact. Good team player Autonomous ...

candidates: Hire and mentor a small team of exceptional engineers and researchers Qualifications You've written and shipped high-performance or SOTA CUDA kernels Deep understanding of mixed precision, quantisation (INT4, INT8, FP8, MXFP4, block-scaled formats), kernel fusion, distributed computing strategies (TP, PP, CP) You've made deliberate … what makes variation operators work on hard combinatorial problems You're familiar with new or esoteric technical methods such as Neural Algorithmic Reasoning, Geometric Deep Learning, Category Theory, Neuroevolution, Megakernels, or the work of François Chollet, Kenneth Stanley, Jeff Clune, Jurgen Schmidhuber, David Ha, and Christian Szegedy Bonus ...

organizations as well as Mobile Apps and Service companies. Required Skills: 2-4 years of experience manipulating data sets and building statistical and machine learning models. Masters or Ph D in Statistics, Mathematics, Computer Science, or another quantitative field Fluent English (written/spoken) Strong hands-on experience … Python, SQL, No SQL. Experience in Developing Machine Learning/Data Science models, from coding to deployment. Preferred Skills: Hands on experience in coding (mandatory python and SQL or C++). Understanding of Generative AI, Computer Vision cloud technology, NLP, Deep Learning. Familiarity working with large data sets. ...

other core computer vision tasks. Your strategic vision and technical expertise will be essential in supporting Ultralytics' mission of delivering top-tier machine learning tools and models like YOLO11 to the community. 🛠️ Skills and Experience 5+ years of hands-on experience in Computer Vision and Deep Learning. Expert … level proficiency in Python and deep expertise with PyTorch. Strong practical experience with OpenCV for image and video processing tasks. Proven experience in training, fine-tuning, and deploying object detection models, particularly within the YOLO family. Familiarity with model optimization techniques such as quantization and pruning, and deployment frameworks ...