1 to 25 of 46 Deep Learning Jobs in Central London

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 ❯

Innovation Hub Build and mentor multidisciplinary teams of data scientists and ML experts Develop and deploy AI use cases that solve real commercial problems Design and implement scalable machine learning, NLP, and deep learning models Work cross-functionally with product, tech, and business stakeholders to drive data-first decision making Build data pipelines, predictive models, and advanced … What We're Looking For: 10+ years of data science experience, with 5+ years in a leadership capacity Proven ability to manage complex, multidimensional teams in fast-paced environments Deep technical understanding of AI, machine learning, deep learning, and LLMs Strong track record of guiding AI strategy and deploying models at scale Exceptional communication and stakeholder More ❯

Principal Data Scientist | Series B | FinTech | SaaS | Scale-Up Location: London Area, United Kingdom (Hybrid) Salary: Up to £140,000 + Equity Skills: Machine Learning | AI | Product ML | Deep Learning | Data Platforms Our client is a rapidly scaling Series B FinTech SaaS business backed by leading VCs. Their platform is used by top financial institutions, digital banks … with Engineering, Product, and GTM teams to build scalable, production-grade AI that directly impacts customers and revenue. This is a hands-on leadership role where you’ll combine deep technical expertise with product thinking, experimentation, stakeholder influence, and team mentorship. What You’ll Be Responsible For Technical Leadership & Strategy Define and own the Data Science roadmap across the … Series B product suite. Architect scalable ML systems and end-to-end pipelines that integrate directly into the core SaaS platform. Evaluate emerging models, large language models (LLMs), and deep learning techniques to drive innovation in the FinTech domain. Hands-On Modelling & Delivery Build, train, validate, and deploy ML solutions across risk modelling, anomaly detection, personalisation, optimisation, and More ❯

into actionable commercial insights and deploying advanced data-science solutions. We develop projects based on innovative ideas or manual processes that can be scaled or automated using data, machine learning, and generative AI. This position has a global remit and plays a key role in influencing strategic decisions through advisory support and high-impact analytical services. We are seeking … intelligence and analytics strategy. You will be responsible for identifying, evaluating, and mitigating risks associated with AI solutions, while also contributing to the design and assessment of novel machine-learning and deep-learning techniques. Key Responsibilities Partner with cross-functional teams—including commercial, analytics, and technology groups—to design, build, deploy, and manage end-to-end generative … to model user behaviour and improve AI performance. Stay current with emerging trends in generative AI, conversational design, and automation. What We’re Looking For Advanced expertise in machine learning, deep learning, and AI, with experience delivering complex, production-ready solutions. Strong Python skills; experience with frameworks such as FastAPI is a plus. Prior experience designing or More ❯

AI/Deep Learning Engineers – Defence Hardware Integration Location: London (with on-site requirements) Clearance: Active SC or SC eligibility required We are supporting a cutting-edge AI research and development organisation working at the intersection of machine learning and defence technology. The team builds and deploys advanced AI models directly into operational hardware systems across land … Multi-sensor fusion (acoustic, optical, and underwater sensing) Computer Vision and Machine Vision systems Real-time model deployment onto embedded and edge hardware Key Responsibilities: Build, train, and optimise deep learning models for deployment on resource-constrained hardware Integrate AI systems into embedded and defence-focused platforms Work cross-functionally with hardware and software teams to ensure robust … system deployment Contribute to the development of next-generation defence AI systems that operate reliably and securely in the field Required Skills & Experience: Proven expertise in deep learning/neural network development (e.g. PyTorch, TensorFlow) Experience deploying models onto embedded devices or edge hardware Understanding of model optimisation techniques (e.g. quantisation, pruning, hardware acceleration) Strong Python and/ 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

managing credit risk to decoding customer behaviour and building smarter banking tools. You could become: • A Data & AI Scientist uncovering insights, making predictions and solving complex problems with machine learning techniques. Always with an ethical and accurate lens. • A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI … biggest datasets in the UK — using everything from Spark and statistical methods to domain knowledge and emerging GenAI applications. The work you could be doing • Design and deploy machine learning models for fraud detection, credit risk, customer segmentation, and behavioural analytics using scalable frameworks like TensorFlow, PyTorch, and XGBoost. • Engineer robust data pipelines and ML workflows using Apache Spark … Vertex AI, and CI/CD tooling to ensure seamless model delivery and monitoring. • Apply advanced techniques in deep learning, natural language processing (NLP), and statistical modelling to extract insights and drive decision-making. • Explore and evaluate Generative AI applications, including prompt engineering, fine-tuning, and safety alignment using tools like Gemini, Claude, and OpenAI APIs. • Design agentic More ❯

quickly embed within the organisation, lead complex projects, and provide advanced analytical insights that drive measurable business outcomes. Key Responsibilities Model Development & Deployment: Design, build, and deploy scalable machine learning and statistical models for use cases such as pricing optimisation, customer behaviour prediction, and risk modelling. Data Exploration & Feature Engineering: Work with structured and unstructured data to uncover patterns … models. Stakeholder Engagement: Collaborate with Technology, Product, Risk, and Marketing teams to translate business challenges into actionable data science solutions. Innovation & Best Practices: Apply cutting-edge techniques in machine learning, deep learning, and generative AI where appropriate. Ensure models meet standards for fairness, transparency, and compliance. Performance Monitoring: Implement model evaluation frameworks and monitor performance in production … environments. Knowledge Transfer: Document processes and share insights to enable continuity post-contract. Skills & Experience Required Advanced degree (Master’s or PhD) in Data Science, Machine Learning, Statistics, Computer Science, or related field. 5+ years of experience in data science roles, with proven expertise in: Machine learning (supervised/unsupervised), time series forecasting, deep learning. Programming in More ❯

Machine Learning Research Engineer Location: London (Hybrid) Salary: Competitive + Benefits We’re working with a rapidly growing AI company developing cutting-edge technology that enhances real-time voice and audio communication. Their products use advanced deep learning and signal processing techniques to isolate speech and remove background noise, improving clarity and focus across a range of … industries, from enterprise software to high-performance environments. They’re now looking for a Machine Learning Research Engineer to join their R&D team in London. The successful candidate will work at the intersection of machine learning, signal processing, and real-time systems , developing and deploying novel models that push the limits of audio intelligence. Responsibilities: Research and … prototype deep learning models for speech enhancement and separation. Design and optimise training pipelines using large-scale audio datasets. Collaborate with engineering teams to deploy models into real-world, low-latency environments. Stay up to date with new research and contribute to the company’s IP. Requirements: Background in audio or speech-related ML (e.g., noise suppression, source More ❯

present tailored AI solutions with real-world impact, not just slideware. Build trust with clients through proof of value and live examples of implemented solutions. Required Technical Skills Machine Learning , Deep Learning , Natural Language Processing , Computer Vision , Generative AI , Reinforcement Learning , LLMs (e.g., GPT, Claude, Mistral, LLaMA, DeepSeek, etc.). Agent-based architectures , RAG , prompt engineering More ❯

x Senior Data Scientists | London | Financial Services 📍 London (Hybrid) 💰 Up to £100,000 + Equity + Private Health 🧑 💻 Machine Learning | Data Science Libraries | Deep Learning Frameworks | AI Our client partners with some of the world’s leading financial institutions to deliver innovative, data-driven solutions that transform decision-making and operational performance. From major banks and asset … managers to insurers and fintech disruptors, they help their clients harness the power of advanced analytics, machine learning, and AI to stay competitive in a rapidly evolving industry. *If you’re looking for an opportunity to shape the future of applied AI in this sector, this is your chance.* ROLE: Senior Data Scientist We’re looking for 3 x … ready AI. You’ll also act as a trusted advisor to clients, working closely with senior stakeholders to shape strategy and deliver measurable business outcomes. What You’ll Bring 🔥Deep knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). ⚙️Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning More ❯

RESTful API design, authentication/authorization standards, and API lifecycle best practices; familiarity with Microsoft Graph API is a plus. Experience & Knowledge Requirements Good knowledge of generative AI, machine learning, deep learning, natural language processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and … clear and accessible manner. Qualifications: Bachelor (preferably master or PhD) in Computer Science, Artificial Intelligence, Data Science, Statistics, Engineering, or a related technical field. Advanced certifications in AI, machine learning, cloud computing or data engineering are highly advantageous - desirable Professional accounting qualification preferred, however not a requirement - desirable To discuss this or wider Technology roles with our recruitment team More ❯

About Us We are a VC-backed startup focused on behavioural AI, currently in stealth. We are building for retail with a focus on Recommendation Systems, Reinforcement Learning and Generative AI. Our platform is designed from the ground up - no legacy, no patchwork systems - just a clean slate and a clear vision. Our mission is to build products that … customers love by harnessing cutting-edge AI to transform their shopping experience. About the Job We are looking for a Senior Data Scientist with experience in bringing advanced machine learning and data science systems to production to work with our team of industry leading domain experts and engineers. You'll be working across our entire data science stack, from … advanced recommender systems to comprehensive performance analytics. Key Responsibilities: Design and implement scalable machine learning for complex data analysis, optimised recommendations, and predictive modelling. Translate the latest advances in machine learning into impactful solutions and products, from rapid MVPs to fully deployed, production-ready systems. Bring your models to production and optimise for inference in edge computing environments. More ❯

the technical leadership and strategic development of the AI capability, helping drive innovation across the business. 🔧 What You’ll Be Doing Lead the development, optimisation, and deployment of machine learning, deep learning, generative AI, and agentic AI models Design and maintain robust AI and data pipelines , including model monitoring, automation, scalability, and performance improvements Collaborate with cross … value A growth and leadership mindset - confident in driving forward innovation, standards and team development 💼 What You Can Expect Hybrid working with excellent collaboration opportunities A culture built on learning, curiosity, experimentation, and high-quality delivery Ability to influence technical direction and shape long-term AI strategy Opportunity to work with modern tooling, cloud platforms and emerging AI technologies More ❯

a highly skilled AI Engineer to design, develop, and deploy AI-driven solutions that enhance business processes and customer experiences. The ideal candidate will have strong expertise in machine learning, deep learning, and data engineering, with hands-on experience in building scalable AI models. About the Role Design, develop, and deploy autonomous AI agents using frameworks like More ❯

Job Description Role Overview: Apply cutting-edge AI and deep learning methods to communication system challenges. Contribute to high-impact research with opportunities to publish at leading AI or communication venues (NeurIPS, IEEE, etc.). Collaborate closely with our top Cambridge-based researchers and international colleagues. Requirement Preferred Qualifications Currently pursuing (or recently completed) a PhD, preferably in … Electrical Engineering or related quantitative fields. Background in wireless communication systems, e.g., OFDM and MIMO technologies. Track record of related publications or successful projects. Proficiency in Deep Learning frameworks (PyTorch, JAX). Familiarity with advanced AI methods (e.g., transformer models). Excellent scientific communication and teamwork skills. Enthusiasm for innovative research with real-world impact. Join us to More ❯

global financial services firm in the search for a Head of Data Science a strategic and delivery-focused leader who will drive enterprise-wide impact through advanced analytics, machine learning, and generative AI. This is a high-profile opportunity to lead a global team and embed data science into the core of decision-making, product innovation, and operational excellence. … science solutions into production environments at scale. 8+ years in data science, including 3+ years in leadership roles. Advanced degree (Master’s or PhD) in Data Science , Statistics , Machine Learning , Computer Science , Mathematics , or Physics . Deep expertise in supervised/unsupervised learning, time series forecasting, deep learning, and generative AI. Strong programming skills in More ❯

expertise in AI and data science with proven leadership in delivering enterprise-grade AI systems to public and private sector clients. Key Responsibilities Design and architect AI and machine learning solutions across a range of use cases, including predictive analytics, natural language processing, and generative AI. Lead technical delivery teams, providing guidance on best practice, architecture, and development processes. … Contribute to business development activities, including bid writing, client presentations, and proposal delivery. Skills and Experience Required Strong capabilities across a range of AI techniques, including supervised and unsupervised learning, generative AI, deep learning, graph analytics, statistical modelling, time-series forecasting, geospatial analysis, NLP, sentiment analysis, and pattern detection. Excellent communication skills, with the ability to present … within large organisations) through RFI/RFP responses, bid documentation, and client presentations. Hands-on experience with data science platforms such as Databricks , Dataiku , AzureML , or SageMaker , and machine learning frameworks such as TensorFlow , Keras , PyTorch , and scikit-learn . Expertise in cloud platforms ( AWS , Azure , Google Cloud ) and experience deploying solutions using cloud provisioning tools such as Terraform More ❯

startup with the reach of a global investment platform. Our team partners directly with internal investment desks as well as portfolio companies across industries to build and deploy machine learning systems that accelerate decision-making and unlock business value. You’ll design, implement and deploy production-grade AI and ML systems, ranging from NLP pipelines that extract insights from … who want to see their models not just trained, but deployed, adopted, and driving measurable results. What You’ll Do Design and deliver AI systems: Build and deploy machine learning models and data-driven products that directly impact investment decisions and portfolio company performance. Drive measurable impact: Partner with internal desks and portfolio teams to integrate ML products into … cloud platforms, and MLOps best practices to build scalable, reusable solutions. Communicate insights clearly: Distill complex technical findings into concise, actionable narratives for technical and business audiences alike. Keep learning and pushing boundaries: Expand your engineering toolkit across the full ML development lifecycle—from prototyping to deployment—and explore new architectures, tools, and approaches to solving complex, real-world More ❯

and mission-driven impact on the world of sport. The Opportunity: They are now looking for a Senior Applied Researcher/Data Scientist to join a high-performing Machine Learning team that’s building AI solutions at scale for real-world applications in sports. You'll apply state-of-the-art techniques in computer vision and deep learning … globally. Collaborate closely with engineers and data scientists to develop end-to-end solutions that deliver real value to users. Technical Requirements: Strong experience in computer vision and machine learning, especially in areas like: Multi-object tracking Event detection Multi-view geometry Deep learning-based video analysis Proven experience bringing ML products from concept to production at More ❯