1 to 25 of 133 Deep Learning Jobs in London

wide (client site travel required) Clearance: SC Cleared Package: Up to £100,000 base + benefits The Opportunity We’re looking for a Principal Data Science Consultant who combines deep technical capability with a strong consulting mindset. You’ll help clients unlock the value in their data, applying advanced AI, ML, and mathematical modelling techniques to drive measurable business … and beta phases. Act as a trusted advisor to clients – helping them define their digital vision, identify opportunities, and translate data science into tangible value. Design and implement machine learning , deep learning , and large language model (LLM) solutions for real-world business challenges. Bring strong mathematical reasoning and estimation skills to build robust, scalable models. Provide technical … multi-disciplinary teams – often embedded onsite with clients . Drive delivery outcomes with a self-starter mindset , ensuring pace, quality, and client satisfaction. About You Strong background in Machine Learning , Deep Learning , and Large Language Models Solid understanding of mathematics , statistics , and data modelling fundamentals. Proven consulting experience – able to engage clients, manage ambiguity, and deliver under More ❯

wide (client site travel required) Clearance: SC Cleared Package: Up to £100,000 base + benefits The Opportunity We’re looking for a Principal Data Science Consultant who combines deep technical capability with a strong consulting mindset. You’ll help clients unlock the value in their data, applying advanced AI, ML, and mathematical modelling techniques to drive measurable business … and beta phases. Act as a trusted advisor to clients – helping them define their digital vision, identify opportunities, and translate data science into tangible value. Design and implement machine learning , deep learning , and large language model (LLM) solutions for real-world business challenges. Bring strong mathematical reasoning and estimation skills to build robust, scalable models. Provide technical … multi-disciplinary teams – often embedded onsite with clients . Drive delivery outcomes with a self-starter mindset , ensuring pace, quality, and client satisfaction. About You Strong background in Machine Learning , Deep Learning , and Large Language Models Solid understanding of mathematics , statistics , and data modelling fundamentals. Proven consulting experience – able to engage clients, manage ambiguity, and deliver under More ❯

Lead Data Scientist | Life Science | Hybrid (London) Up to £130k + equity We’re partnering with a pioneering health technology company using machine learning and predictive analytics to transform how cardiovascular and metabolic diseases are detected, treated, and ultimately prevented. Their mission is to use AI and data science to extend global health span by identifying individuals at risk … of disease before symptoms occur. You’ll join as the first Data Science hire, building the foundation of a platform that integrates multi-modal biomedical data, deep learning models, and large-scale population datasets such as UK Biobank and Our Future Health. This is a rare opportunity to lead model development in a setting that bridges scientific rigour … with production-grade engineering. Key Responsibilities Design, train, and deploy state-of-the-art machine learning and deep learning models to predict health outcomes and disease progression. Apply advanced statistical and causal inference methods (e.g. survival analysis, time-to-event modelling, propensity scoring, Mendelian randomisation). Analyse and integrate multi-omics and clinical datasets to uncover novel More ❯

Lead Data Scientist | Life Science | Hybrid (London) Up to £130k + equity We’re partnering with a pioneering health technology company using machine learning and predictive analytics to transform how cardiovascular and metabolic diseases are detected, treated, and ultimately prevented. Their mission is to use AI and data science to extend global health span by identifying individuals at risk … of disease before symptoms occur. You’ll join as the first Data Science hire, building the foundation of a platform that integrates multi-modal biomedical data, deep learning models, and large-scale population datasets such as UK Biobank and Our Future Health. This is a rare opportunity to lead model development in a setting that bridges scientific rigour … with production-grade engineering. Key Responsibilities Design, train, and deploy state-of-the-art machine learning and deep learning models to predict health outcomes and disease progression. Apply advanced statistical and causal inference methods (e.g. survival analysis, time-to-event modelling, propensity scoring, Mendelian randomisation). Analyse and integrate multi-omics and clinical datasets to uncover novel More ❯

significant contribution to the design, development, and implementation of advanced AI/ML models, frameworks, and systems. A notable part of the role involves building, training, and optimising machine learning models, including deep learning computer vision models, and fine-tuning natural language processing (NLP), and integrating third party generative AI models. Ideal background: • 3+ years of experience … in machine learning, deep learning or AI engineering • Advanced proficiency in Python and ML frameworks like PyTorch • Experience deploying and maintaining scalable production-grade AI systems • Strong understanding of data pipelines, MLOps and cloud platforms (AWS) • Experience working in small or mid-sized tech/software development environments (rather than in corporate environments) would be advantageous The More ❯

significant contribution to the design, development, and implementation of advanced AI/ML models, frameworks, and systems. A notable part of the role involves building, training, and optimising machine learning models, including deep learning computer vision models, and fine-tuning natural language processing (NLP), and integrating third party generative AI models. Ideal background: • 3+ years of experience … in machine learning, deep learning or AI engineering • Advanced proficiency in Python and ML frameworks like PyTorch • Experience deploying and maintaining scalable production-grade AI systems • Strong understanding of data pipelines, MLOps and cloud platforms (AWS) • Experience working in small or mid-sized tech/software development environments (rather than in corporate environments) would be advantageous The More ❯

themselves. Position Overview: You will join the Entrust Applied Science team as a research intern. The team consists of 20+ Applied Scientists located in London, UK. We develop machine learning and computer vision models for the Onfido product lines, in particular fraud detection and data extraction on government IDs and biometrics data. You will work together with a team … of scientist who will coach and train you during your internship. We use state-of-the-art technology (deep learning, VLMs), own a large proprietary dataset of images and videos and use a multi-GPU cluster. We use standard frameworks (python, pytorch, tensorflow, dask, AWS). We impact production directly but also the machine learning community. Responsibilities … train models on state-of-the-art GPUs Your work will impact products used by dozens of millions of users worldwide You will be mentored by a senior machine learning scientist to make sure you are successful in your mission You will have the opportunity to publish and open-source your work You will be part of a vibrant More ❯

themselves. Position Overview: You will join the Entrust Applied Science team as a research intern. The team consists of 20+ Applied Scientists located in London, UK. We develop machine learning and computer vision models for the Onfido product lines, in particular fraud detection and data extraction on government IDs and biometrics data. You will work together with a team … of scientist who will coach and train you during your internship. We use state-of-the-art technology (deep learning, VLMs), own a large proprietary dataset of images and videos and use a multi-GPU cluster. We use standard frameworks (python, pytorch, tensorflow, dask, AWS). We impact production directly but also the machine learning community. Responsibilities … train models on state-of-the-art GPUs Your work will impact products used by dozens of millions of users worldwide You will be mentored by a senior machine learning scientist to make sure you are successful in your mission You will have the opportunity to publish and open-source your work You will be part of a vibrant More ❯

Research Team, working at the forefront of generative AI and its applications in life sciences. Our team is dedicated to building foundational expertise and developing the next generation of deep learning technologies. Roles are available for both recent graduates and senior profiles. Generative foundation models like ESM-3 1 , AlphaFold 2 , RFDiffusion 3 , ProteinMPNN 4 are revolutionising computational … Develop Biological Foundation Models Contribute to the creation of new models that push the boundaries of what's possible in computational biology. Collaborate Across Disciplines Work closely with Machine Learning Engineers, Research Engineers, Computational Biologists, and other experts. Leverage Cutting-Edge Resources Utilise our near-exascale supercomputing cluster, Kyber 9 , to conduct large-scale training and evaluation of generative … models. Publish and Present Research Share your findings at top-tier conferences and in leading journals. Responsibilities Innovate in Deep Learning Research Develop and implement novel research on multimodal generative foundation models and their biological applications. Contribute to Team Success Collaborate with team members to achieve research goals and contribute to a supportive, knowledge-sharing environment. Engage in More ❯

seeking Applied Research Scientists with expertise in RNA modeling, RNA optimization, or RNA design to join our world-class, multi-disciplinary team. This role sits at the intersection of deep scientific research and practical product development, aimed at building cutting-edge biological AI models and deploying them to researchers advancing the life sciences. Applied Research Scientists at InstaDeep leverage … their deep expertise in scientific principles, artificial intelligence, and computational biology to create more accurate, efficient, and scalable tools that enhance our understanding of biology and accelerate the development of medical treatments, including RNA therapeutics. This position demands close collaboration across AI research, biology, engineering, and business teams, as well as with strategic partners like BioNTech. Success in this … design, optimisation and modelling. Design, implement, and evaluate proof-of-concept methods and benchmarking experiments using state-of-the-art approaches. Leverage both classical computational biology tools and modern deep learning approaches for tasks such as RNA design, optimization, and molecular modeling. Enhance the understanding of AI model behavior in biological applications by contributing to interpretability and performance More ❯

quality, model performance, evaluation, failure modes, and how AI fits into real financial workflows within a modern fintech platform. What You’ll Be Doing: Designing, training, and deploying machine learning and deep learning models for financial analytics, credit/risk scoring, and portfolio insights Building LLM-powered tools (e.g. using GPT-class models) that assist with data … of models in financial contexts What We’re Looking For: A completed AI-focused Master’s degree from a top-tier university such as: MSc Artificial Intelligence, MSc Machine Learning, MSc Data Science with a strong AI/ML track. Or a closely related programme with substantial AI/ML content Strong applied project experience in machine learning or deep learning (thesis, research projects, internships, or substantial personal projects) Excellent Python skills with experience using core AI/ML libraries (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Experience training, tuning, and evaluating models using real datasets (not just toy examples), including careful validation and error analysis Familiarity with modern LLM tooling and workflows (e.g. using More ❯

quality, model performance, evaluation, failure modes, and how AI fits into real financial workflows within a modern fintech platform. What You’ll Be Doing: Designing, training, and deploying machine learning and deep learning models for financial analytics, credit/risk scoring, and portfolio insights Building LLM-powered tools (e.g. using GPT-class models) that assist with data … of models in financial contexts What We’re Looking For: A completed AI-focused Master’s degree from a top-tier university such as: MSc Artificial Intelligence, MSc Machine Learning, MSc Data Science with a strong AI/ML track. Or a closely related programme with substantial AI/ML content Strong applied project experience in machine learning or deep learning (thesis, research projects, internships, or substantial personal projects) Excellent Python skills with experience using core AI/ML libraries (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Experience training, tuning, and evaluating models using real datasets (not just toy examples), including careful validation and error analysis Familiarity with modern LLM tooling and workflows (e.g. using More ❯

or monotonous, we envision a future where human well-being is safeguarded while closing the gaps in critical global labour needs. What You'll Do: Train policies via representation learning, behaviour cloning and RL; own the full loop from data to deployment. Partner with teleoperations to drive data collection: specify what “good” looks like, ensure diversity/coverage, and … failure cases into retraining. Work with MLOps & Data Platform teams to scale distributed training and optimize models for real‐time edge inference. We’re Looking For: 3+ years building deep‐learning systems (industry or research) with shipped models or published artifacts to show for it. Hands‐on with at least one of: LLMs, VLMs, or image/video … generative models — architecture, training, and inference. Experience with deep learning infrastructure: streaming datasets, checkpointing & state management, distributed training strategies. Strong Python + PyTorch/JAX; you can profile, debug numerics, and write maintainable research code. You document experiments clearly and communicate trade‐offs crisply. Nice-to-Have: Robotics or autonomous driving experience. RL for LLMs or robotics (PPO More ❯

or monotonous, we envision a future where human well-being is safeguarded while closing the gaps in critical global labour needs. What You'll Do: Train policies via representation learning, behaviour cloning and RL; own the full loop from data to deployment. Partner with teleoperations to drive data collection: specify what “good” looks like, ensure diversity/coverage, and … failure cases into retraining. Work with MLOps & Data Platform teams to scale distributed training and optimize models for real‐time edge inference. We’re Looking For: 3+ years building deep‐learning systems (industry or research) with shipped models or published artifacts to show for it. Hands‐on with at least one of: LLMs, VLMs, or image/video … generative models — architecture, training, and inference. Experience with deep learning infrastructure: streaming datasets, checkpointing & state management, distributed training strategies. Strong Python + PyTorch/JAX; you can profile, debug numerics, and write maintainable research code. You document experiments clearly and communicate trade‐offs crisply. Nice-to-Have: Robotics or autonomous driving experience. RL for LLMs or robotics (PPO More ❯

design, optimization of NLP systems, frameworks, and tools. Application Development with LLMs: Experience in building scalable applications using LLMs, utilizing frameworks such as LangChain, LlamaIndex, etc and productionizing machine learning and AI models. Language Model Development: Utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications. Cloud Computing Expertise: Proven architect kind of … cloud computing, particularly with Azure Cloud Services. Technical Proficiency: Strong skills in UNIX/Linux environments and command-line tools. Programming and ML Skills: Proficiency in Python, with a deep understanding of machine learning algorithms, deep learning, and generative models. Advanced AI Skills and Testing: Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch), hands More ❯

design, optimization of NLP systems, frameworks, and tools. Application Development with LLMs: Experience in building scalable applications using LLMs, utilizing frameworks such as LangChain, LlamaIndex, etc and productionizing machine learning and AI models. Language Model Development: Utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications. Cloud Computing Expertise: Proven architect kind of … cloud computing, particularly with Azure Cloud Services. Technical Proficiency: Strong skills in UNIX/Linux environments and command-line tools. Programming and ML Skills: Proficiency in Python, with a deep understanding of machine learning algorithms, deep learning, and generative models. Advanced AI Skills and Testing: Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch), hands More ❯

and the other dedicated to fundamental research that supports both our applications and the broader scientific community. Current areas of interest include large language models (LLMs), optimization methods for deep learning, reinforcement learning (RL), and generative models. Responsibilities:- Contribute to ongoing research in machine learning and artificial intelligence Help develop and implement algorithms Collaborate with researchers … preparing publications and technical reports Stay up to date with the latest advancements in AI and related fields Requirement Qualifications Required: Currently enrolled in a PhD program in Machine Learning, Artificial Intelligence, Mathematics, Computer Science, Physics, or a related field Strong interest in research and a background in machine learning or a related area Experience with programming languages … similar Strong problem-solving skills and ability to work independently and collaboratively Good communication skills and ability to present complex ideas clearly Nice-to-have Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) Previous research publications or submitted papers Why Join Us Gain hands More ❯

ASAP | Outside IR35 To apply, email: THE OPPORTUNITY A new contract opportunity for an AI Engineer to join a cutting-edge AI Sports company revolutionising how data and machine learning drive athletic performance, fan engagement, and predictive analytics in the sports industry. You'll be part of a highly skilled R&D team building next-generation AI solutions for … real-world data into actionable insights. Optimise AI systems for real-time environments, integrating with live data feeds and cloud infrastructure. Research and prototype cutting-edge AI techniques (e.g., deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn … Experience with wearable/sensor data, player tracking, or sports video analytics TO BE CONSIDERED Please apply directly by emailing with your CV and availability. KEYWORDS: AI Engineer, Machine Learning Engineer, Sports Analytics, Computer Vision, Deep Learning, Python, TensorFlow, PyTorch, MLOps, Data Science, Predictive Modelling, Sports Tech, AI in Sports More ❯

IR35 To apply, email: jordanna.ramsey@searchability.com THE OPPORTUNITY A new contract opportunity for an AI Engineer to join a cutting-edge AI Sports company revolutionising how data and machine learning drive athletic performance, fan engagement, and predictive analytics in the sports industry. You’ll be part of a highly skilled R&D team building next-generation AI solutions for … real-world data into actionable insights. Optimise AI systems for real-time environments, integrating with live data feeds and cloud infrastructure. Research and prototype cutting-edge AI techniques (e.g., deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn … wearable/sensor data, player tracking, or sports video analytics TO BE CONSIDERED... Please apply directly by emailing jordanna.ramsey@searchability.com with your CV and availability. KEYWORDS: AI Engineer, Machine Learning Engineer, Sports Analytics, Computer Vision, Deep Learning, Python, TensorFlow, PyTorch, MLOps, Data Science, Predictive Modelling, Sports Tech, AI in Sports More ❯

IR35 To apply, email: jordanna.ramsey@searchability.com THE OPPORTUNITY A new contract opportunity for an AI Engineer to join a cutting-edge AI Sports company revolutionising how data and machine learning drive athletic performance, fan engagement, and predictive analytics in the sports industry. You’ll be part of a highly skilled R&D team building next-generation AI solutions for … real-world data into actionable insights. Optimise AI systems for real-time environments, integrating with live data feeds and cloud infrastructure. Research and prototype cutting-edge AI techniques (e.g., deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn … wearable/sensor data, player tracking, or sports video analytics TO BE CONSIDERED... Please apply directly by emailing jordanna.ramsey@searchability.com with your CV and availability. KEYWORDS: AI Engineer, Machine Learning Engineer, Sports Analytics, Computer Vision, Deep Learning, Python, TensorFlow, PyTorch, MLOps, Data Science, Predictive Modelling, Sports Tech, AI in Sports More ❯

Lead AI Research Engineer – Defence Technology | Machine Learning | Robotics | London The Opportunity As Lead AI Research Engineer , you’ll take ownership of designing and delivering cutting-edge AI and machine learning solutions that power real-world autonomous systems. You’ll lead a small, high-performing team of AI engineers while remaining hands-on, tackling some of the toughest … technical challenges in computer vision, multi-modal sensing, control systems, deep learning, and real-time inference . You’ll play a key role in shaping both the technical direction and the AI strategy — from research and model development to deployment on drones, ground robots, and edge devices. Key Responsibilities Build, lead, and mentor a high-performing AI and … Machine Learning engineering team . Design, implement, and optimise AI/ML models for perception, decision-making, and control. Integrate AI algorithms into both enterprise-scale and edge-deployed systems . Work with customers to translate complex problems into AI-powered solutions . Lead on data strategy , from collection and simulation to training and validation. Ensure AI safety, ethics More ❯

Lead AI Research Engineer – Defence Technology | Machine Learning | Robotics | London The Opportunity As Lead AI Research Engineer , you’ll take ownership of designing and delivering cutting-edge AI and machine learning solutions that power real-world autonomous systems. You’ll lead a small, high-performing team of AI engineers while remaining hands-on, tackling some of the toughest … technical challenges in computer vision, multi-modal sensing, control systems, deep learning, and real-time inference . You’ll play a key role in shaping both the technical direction and the AI strategy — from research and model development to deployment on drones, ground robots, and edge devices. Key Responsibilities Build, lead, and mentor a high-performing AI and … Machine Learning engineering team . Design, implement, and optimise AI/ML models for perception, decision-making, and control. Integrate AI algorithms into both enterprise-scale and edge-deployed systems . Work with customers to translate complex problems into AI-powered solutions . Lead on data strategy , from collection and simulation to training and validation. Ensure AI safety, ethics More ❯

Machine Learning Engineer (LLM/AI Systems) London/Hybrid | 0–3 Years Experience | Competitive Salary Are you obsessed with AI and large language models? We’re an early-stage startup building real-world products powered by LLMs — from intelligent copilots to adaptive automation tools — and we’re looking for curious minds to help us shape the future of … edge of ML/AI research — we give you time and resources to explore, learn, and publish. What We’re Looking For 0–3 years of experience in Machine Learning, Data Science, or NLP/LLM. Strong Python skills; exposure to PyTorch/TensorFlow/Hugging Face. (Bonus) understand fundamentals of deep learning, LLMs, and MLOps, vector … Flexible working — remote-first culture with in-person team sessions for collaboration. Career acceleration — opportunities to own projects, lead development, and shape the product roadmap. An environment that values learning, creativity, and personal growth over bureaucracy. Perfect For Graduates or junior engineers with a passion for AI/ML looking to break into applied LLM engineering. Researchers or data More ❯

The team leverages technology and AI to enhance, not replace, human creativity and insight. Responsibilities - Lead end-to-end execution of complex data science projects integrating statistical modelling, machine learning (ML), and deep learning (DL). - Collaborate closely with cross-functional teams (product, engineering, business stakeholders) to deliver data-driven solutions. - Design and conduct hypothesis testing (A …/B and multivariate testing) and apply causal inference methodologies. - Perform exploratory data analysis, feature engineering, and develop models across traditional statistical and deep learning architectures. - Establish modelling frameworks with statistical quality control, detecting drift and decay. - Drive best practices for model explainability (e.g., SHAP/LIME) and scalable ML systems (including generative AI, NLP, CV, and recommendation … years in data science with at least 2 years leading teams. - Proven success in production deployment of ML/LLM/NLP/CV models. - Strong understanding of machine learning fundamentals, statistical inference, and model evaluation. - Advanced proficiency in SQL (e.g., PostgreSQL, ELT/ETL) and Python (PyTorch, LightGBM, Scikit-learn). - Experience with modern AI concepts: prompt engineering More ❯

The team leverages technology and AI to enhance, not replace, human creativity and insight. Responsibilities - Lead end-to-end execution of complex data science projects integrating statistical modelling, machine learning (ML), and deep learning (DL). - Collaborate closely with cross-functional teams (product, engineering, business stakeholders) to deliver data-driven solutions. - Design and conduct hypothesis testing (A …/B and multivariate testing) and apply causal inference methodologies. - Perform exploratory data analysis, feature engineering, and develop models across traditional statistical and deep learning architectures. - Establish modelling frameworks with statistical quality control, detecting drift and decay. - Drive best practices for model explainability (e.g., SHAP/LIME) and scalable ML systems (including generative AI, NLP, CV, and recommendation … years in data science with at least 2 years leading teams. - Proven success in production deployment of ML/LLM/NLP/CV models. - Strong understanding of machine learning fundamentals, statistical inference, and model evaluation. - Advanced proficiency in SQL (e.g., PostgreSQL, ELT/ETL) and Python (PyTorch, LightGBM, Scikit-learn). - Experience with modern AI concepts: prompt engineering More ❯