1 to 25 of 725 Deep Learning Jobs in London

play a key role in analyzing our data and designing models that enhance our AI-powered analytics capabilities. You'll work alongside our skilled team of engineers and machine learning experts, directly contributing to next-generation capabilities that enable our users to automate their PAI collection and analysis workflows. This role is crucial to our mission of making the … insights that can enhance our platform's capabilities. Research and evaluate algorithms for information discovery from publicly available sources. Design advanced search and recommendation capabilities. Create and refine machine learning models for risk identification and pattern detection. Collaborate with engineers to integrate your data science solutions into our platform. Design and analyze A/B tests to measure the … . Strong programming skills in Python, with proficiency in data science libraries (NumPy, Pandas, scikit-learn). Experience with SQL for data querying and analysis. Solid understanding of machine learning algorithms, statistical methods, and predictive modeling. Experience with NLP techniques for text analysis, classification, and information extraction. Knowledge of deep learning frameworks such as PyTorch or TensorFlow. More ❯

Social network you want to login/join with: Junior Machine Learning Engineer - AI startup, west london col-narrow-left Client: Founding Teams Location: west london, United Kingdom Job Category: Other - EU work permit required: Yes col-narrow-right Job Views: 4 Posted: 16.06.2025 Expiry Date: 31.07.2025 col-wide Job Description: Founding Teams is a stealth AI Tech Incubator … a passion for next generation AI tech startups and working with great global startup talent. About the Role: We are looking for an experienced and highly motivated Lead Machine Learning Engineer to drive the development, deployment, and optimization of machine learning solutions. As a technical leader, you will collaborate closely with data scientists, software engineers, and product managers … to bring cutting-edge ML models into production at scale. You'll play a key role in shaping the AI strategy and mentoring the machine learning team. Responsibilities: Lead the end-to-end development of machine learning models, from prototyping to production deployment. Architect scalable ML pipelines and infrastructure. Work closely with data scientists to transition research models More ❯

Social network you want to login/join with: Junior Machine Learning Engineer - AI startup, south west london col-narrow-left Client: Founding Teams Location: south west london, United Kingdom Job Category: Other - EU work permit required: Yes col-narrow-right Job Views: 4 Posted: 16.06.2025 Expiry Date: 31.07.2025 col-wide Job Description: Founding Teams is a stealth AI … a passion for next generation AI tech startups and working with great global startup talent. About the Role: We are looking for an experienced and highly motivated Lead Machine Learning Engineer to drive the development, deployment, and optimization of machine learning solutions. As a technical leader, you will collaborate closely with data scientists, software engineers, and product managers … to bring cutting-edge ML models into production at scale. You'll play a key role in shaping the AI strategy and mentoring the machine learning team. Responsibilities: Lead the end-to-end development of machine learning models, from prototyping to production deployment. Architect scalable ML pipelines and infrastructure. Work closely with data scientists to transition research models More ❯

through expertise in data strategy, data analytics, decision sciences, and data engineering and infrastructure. This position is within our decision sciences practice which focuses on delivering solutions via machine learning and statistical modelling. What you will do As a part of Aimpoint Digital, you will focus on enabling clients to get the most out of their data. You will … of the client organization to build value driving solutions that extract insights and then train them on how to manage and maintain these solutions. Typical solutions will utilize machine learning, artificial intelligence, statistical analysis, automation, optimization, and/or data visualizations. As a Lead Data Scientist, you will be expected to work independently on client engagements, take part in … simple, elegant solutions as well as cutting-edge solutions that, regardless of complexity, your clients can understand, implement, and maintain. You genuinely think about the end-to-end machine learning pipeline as you generate robust solutions. You are both a teacher and a student as we enable our clients, upskill our teammates, and learn from one another. You want More ❯

helping define product strategy. In this role, you will: Lead AI strategy and execution in a high-ambiguity environment. Build, train, and deploy state-of-the-art models (e.g., deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures). Design infrastructure for data ingestion, annotation, experimentation, model versioning, and monitoring. Collaborate closely with product … helping define product strategy. In this role, you will: Lead AI strategy and execution in a high-ambiguity environment. Build, train, and deploy state-of-the-art models (e.g., deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures). Design infrastructure for data ingestion, annotation, experimentation, model versioning, and monitoring. Collaborate closely with product … quarter AI roadmap aligned with product milestones and fundraising milestones. Identify and evaluate opportunities for AI-driven competitive advantages (e.g., proprietary data, unique model architectures, transfer/few-shot learning). Collaborate with business stakeholders to translate “big problems” into technically feasible AI solutions. Data & Infrastructure Oversee the creation and maintenance of scalable data pipelines (ETL/ELT) and More ❯

your team and other members of the service line cross-skilling Leadership role(s) within internal innovation initiative, including development of prototype or demo solutions, mathematical models, algorithms, machine learning techniques, and robust analytics to support analytic insights and visualization of complex data sets Provide Thought Leadership within the service by exploring new experimentation methods and statistical techniques that … good fit! General technical requirements: BSc, MSc, or PhD in Mathematics, Statistics, Computer Science, Engineering, Operations Research, Econometrics, or related fields Strong knowledge of Probability Theory, Statistics, and a deep understanding of the Mathematics behind Machine Learning Proficiency with CRISP-ML(Q) or TDSP methodologies for addressing commercial problems through data science or AI solutions Hands-on experience … with various machine learning techniques, including but not limited to: Regression Classification Dimensionality reduction LLM Proficiency in Python for developing machine learning models and conducting statistical analyses Strong understanding of data visualization tools and techniques (e.g., Python libraries such as Matplotlib, Seaborn, Plotly, etc.) and the ability to present data effectively Specific technical requirements: Data Science or AI More ❯

Job Description Department: Information Technology Job Summary We are seeking a highly skilled and motivated Data Scientist with a strong focus on machine learning (ML) and artificial intelligence (AI) to join our innovative team. The ideal candidate will excel in developing, deploying, and optimizing ML models and AI solutions, leveraging cutting-edge technologies like Azure Machine Learning, AutoML … based AI tools. This role is essential for driving insights, automating processes, and delivering impactful business outcomes. Key Responsibilities ML and AI Model Development Design, build, and deploy machine learning models using advanced algorithms, including AutoML techniques. Develop and fine-tune models for regression, classification, clustering, and deep learning. Explore and implement state-of-the-art AI approaches … Insights Extract actionable insights from structured and unstructured datasets to support strategic decision-making. Use predictive and prescriptive analytics to solve business challenges. Technology and Tools Utilize Azure Machine Learning and AI tools to manage model lifecycles. Leverage cloud platforms like Azure, AWS, and GCP for scalable ML model deployment. Employ frameworks like TensorFlow, PyTorch, and scikit-learn for More ❯

digital transformation, and engineering solutions. With a strong global presence, this organization empowers businesses across industries such as banking, healthcare, manufacturing, and telecom. It fosters a culture of innovation, learning, and growth, making it an excellent workplace for tech professionals. Join us to be part of a dynamic team driving impactful solutions worldwide! Job Description: We are seeking a … data storage, processing, and retrieval. Ensure the system's scalability, 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 … with data scientists and engineers to ensure the quality and relevance of data for AI model training. Model Training and Evaluation: Train AI models using supervised, unsupervised, or reinforcement learning techniques. 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 More ❯

Research and develop cutting edge Machine Learning & Natural Language Processing methodologies to find more untreated patients London Technical Pangaea Data (Pangaea) is a South San Francisco and London based business founded by Dr Vibhor Gupta and Prof Yike Guo (Director Data Science Institute at Imperial College London; Provost, Hong Kong University of Science and Technology). They have worked … team to develop and productize cutting-edge AI algorithms for Pangaea's core AI platform, PALLUX. This role requires a strong foundation in software engineering, and expertise in Machine Learning (ML), including Natural Language Processing (NLP). This role is an excellent opportunity for an individual who is passionate about innovation and eager to be part of a fast … paced environment that encourages continuous learning and growth. Key Responsibilities Technical Responsibilities: Collaborate with internal clinicians and project stakeholders to understand the clinical and healthcare challenges that Pangaea Data can address through its PALLUX platform and solutions Maintain and implement the product roadmap according to respective requirements Design and adopt cutting-edge ML and NLP algorithms to address real More ❯

including support for customers who require specialized security solutions for their cloud services. Are you an inventive, curious, and driven Applied Scientist with a strong background in AI and Deep Learning? Join Amazon's AWS Multimodal generative AI science team and be a catalyst for groundbreaking advancements in Computer Vision, Generative AI, and foundational models. As part of … to products that redefine the industry. Key job responsibilities Lead research initiatives in Multimodal generative AI, pushing the boundaries of model efficiency, accuracy, and scalability. Design, implement, and evaluate deep learning models in a production environment. Collaborate with cross-functional teams to transfer research outcomes into scalable AWS services. Publish in top-tier conferences and journals, keeping Amazon … Science, Electrical Engineering, Statistics, Mathematics, or a related field. Proven expertise in AI/ML fields such as LLMs, Computer Vision, Generative AI, NLP, or foundational models. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and familiarity with cloud-based computing platforms. Strong analytical, mathematical, and coding skills (e.g., Python, C++, or Java). First author in research More ❯

Services team is looking for a Data Scientist, this role plays a crucial role in delivering the generative artificial intelligence (GenAI) solutions for our clients. This position requires a deep understanding of machine learning, natural language processing, and generative models, combined with problem-solving skills and a passion for innovation. Possessing a deep understanding of AWS products … knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. BASIC QUALIFICATIONS - Master's or Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field. - 4+ years of experience in developing and deploying machine learning models, with a strong focus on generative AI techniques. - Proficiency in … programming languages such as Python, PyTorch, or TensorFlow, and experience with deep learning frameworks. - Strong background in natural language processing, computer vision, or multimodal learning. - Ability to communicate technical concepts to both technical and non-technical audiences. PREFERRED QUALIFICATIONS - Experience with large language models, such as Claude, GPT, BERT, or T5. - Familiarity with reinforcement learning techniques and More ❯

be based on your skills and experience — talk with your recruiter to learn more. Base pay range Direct message the job poster from Harnham Building Data Science and Machine Learning Teams in the UK | The Talent Driving The Data and AI Revolution Principal Data Scientist Up to £125,000 London (Hybrid, 3 days onsite per week) Company: A leading … marketing and analytics agency is seeking a Lead Data Scientist to develop and deploy end-to-end AI solutions. You'll work on machine learning models for retention, price optimisation, recommendation engines, NLP, and Computer Vision. Responsibilities: Design, develop, and productionize machine learning models across various applications. Work with Python (ideally production-level code) and other tools like … SQL, Spark, and Databricks. Apply clustering, classification, regression, time series modelling, NLP, and deep learning. Develop recommendation engines and leverage third-party data enhancements. Implement MLOps/DevOps practices in cloud environments (AWS, Azure, GCP). Ensure explainability, bias detection, and algorithmic fairness in models. Collaborate with stakeholders to translate business challenges into data-driven solutions. Requirements: MSc or More ❯

job and more exclusive features. Direct message the job poster from HR Ways - Hiring Tech Talent HR Generalist | Tech Recruiter | Executive Search | HR Operations | Payroll Specialist Hiring Sr. Machine Learning Engineer - Hybrid in London, UK Client Introduction: The company is a multinational Sweden SAAS product-based firm. Company Strength: 100+ Job Description: Design and implement Graph Neural Network (GNN … customer-facing stakeholders. Required Qualifications: Bachelors degree in computer science, Mathematics or a related technical field or equivalent practical experience. Certifications Minimum: Google Professional Data Engineer Preferred: AWS Machine Learning Specialty Certification 7+ years in a customer facing role working with enterprise clients 4+ years of experience working in enterprise data warehouse and analytics technologies Hands-on experience building … and training machine learning models. Experience writing software in one or more languages such as Python, Scala, R, or similar with strong competencies in data structures, algorithms, and software design. Experience working with recommendation engines, data pipelines, or distributed machine learning. Experience working with deep learning frameworks (such as TensorFlow, Keras, Torch, Caffe, Theano). Strong coding More ❯

Get AI-powered advice on this job and more exclusive features. Infosys Consulting is a leading innovator in the tech industry, specializing in artificial intelligence and machine learning solutions. We work with a diverse range of clients to deliver cutting-edge AI technologies that drive business growth and innovation. We are looking for a talented Machine Learning/… and help us build the future of AI. Key Responsibilities: Collaborate with clients to understand their business needs and translate them into technical requirements Design, develop, and deploy machine learning and generative AI models, including but not limited to NLP models, computer vision models, and reinforcement learning systems Conduct research and stay updated on the latest advancements in … AI and machine learning technologies, particularly in generative models such as GANs, VAEs, and diffusion models Analyze large datasets to uncover patterns, insights, and opportunities for machine learning applications Optimize and fine-tune models for performance, scalability, and accuracy Build and maintain scalable data pipelines for model training and deployment Provide technical guidance and mentorship to junior data More ❯

Kingdom Work Mode: On-Site Seeking a senior/lead data scientist to be part of a team that will be dedicated to build and support Generative AI, Machine learning, Deep Learning and Data science solutions across the organization. Specific Emerging Technology team objectives are: Gen AI/ML technology implementation with business and product owners Emerging … role with significant visibility where the candidate will work on some flagship products The candidate will have an excellent opportunity to work in the cutting-edge field of machine learning and data science promotes an excellent work culture and is known for providing a good work life balance The successful candidate will lead the development and implementation of innovative … integrate, and deploy GenAI and data science solutions. Ensure sharing best practices and learnings with other squad members. Lead and manage development and research projects focused on generative AI, deep learning, machine learning, NLP, and large language models. Design, develop, and deploy state-of-the-art machine learning models and algorithms that leverage deep learning More ❯

grade workloads , focusing on efficiency, adaptability, and security . Algorithm & Model Development Develop and optimize AI algorithms for predictive analytics, recommendation engines, and automation in professional services. Apply machine learning (ML) and deep learning (DL) techniques to enhance decision-making and business intelligence. Data Engineering & Integration Architect robust data pipelines to support AI model training and inference. … inputs. Collaborate with data engineering teams to align AI solutions with real-world business applications. AI Model Training, Evaluation & Performance Optimization Train AI models using supervised, unsupervised, and reinforcement learning techniques , refining them based on business insights . Define model performance metrics to ensure AI solutions deliver tangible value. Real-Time AI Applications & System Integration Work alongside software engineers … for AI model development and deployment. Familiarity with AI libraries and frameworks (TensorFlow, PyTorch, Keras). Experience deploying AI models in cloud computing environments (AWS, Azure, Google Cloud). Deep understanding of enterprise AI architecture, data engineering, and model optimization . Strong problem-solving skills, with a business-driven approach to AI implementation. Effective communication and collaboration skills in More ❯

grade workloads , focusing on efficiency, adaptability, and security . Algorithm & Model Development Develop and optimize AI algorithms for predictive analytics, recommendation engines, and automation in professional services. Apply machine learning (ML) and deep learning (DL) techniques to enhance decision-making and business intelligence. Data Engineering & Integration Architect robust data pipelines to support AI model training and inference. … inputs. Collaborate with data engineering teams to align AI solutions with real-world business applications. AI Model Training, Evaluation & Performance Optimization Train AI models using supervised, unsupervised, and reinforcement learning techniques , refining them based on business insights . Define model performance metrics to ensure AI solutions deliver tangible value. Real-Time AI Applications & System Integration Work alongside software engineers … for AI model development and deployment. Familiarity with AI libraries and frameworks (TensorFlow, PyTorch, Keras). Experience deploying AI models in cloud computing environments (AWS, Azure, Google Cloud). Deep understanding of enterprise AI architecture, data engineering, and model optimization . Strong problem-solving skills, with a business-driven approach to AI implementation. Effective communication and collaboration skills in More ❯

grade workloads , focusing on efficiency, adaptability, and security . Algorithm & Model Development Develop and optimize AI algorithms for predictive analytics, recommendation engines, and automation in professional services. Apply machine learning (ML) and deep learning (DL) techniques to enhance decision-making and business intelligence. Data Engineering & Integration Architect robust data pipelines to support AI model training and inference. … inputs. Collaborate with data engineering teams to align AI solutions with real-world business applications. AI Model Training, Evaluation & Performance Optimization Train AI models using supervised, unsupervised, and reinforcement learning techniques , refining them based on business insights . Define model performance metrics to ensure AI solutions deliver tangible value. Real-Time AI Applications & System Integration Work alongside software engineers … for AI model development and deployment. Familiarity with AI libraries and frameworks (TensorFlow, PyTorch, Keras). Experience deploying AI models in cloud computing environments (AWS, Azure, Google Cloud). Deep understanding of enterprise AI architecture, data engineering, and model optimization . Strong problem-solving skills, with a business-driven approach to AI implementation. Effective communication and collaboration skills in More ❯

investor communications, and software product development, onboarding, and support. As the AI Architect, you will be driving innovation and play a crucial role in designing, developing, and deploying machine learning models and applying GenAI technologies in AI solutions across various business functions. The focus of this role includes the entire model development lifecycle, with an emphasis on MLOps practices … AI, LLMOps, and AI agents is required to drive advanced AI functionalities within our organization. Join our dynamic team and be part of a collaborative environment that fosters continuous learning and creativity. If you are an experienced AI Engineer and passionate about machine learning, GenAI, and want to contribute to high impact AI projects in Financial Services, we … and capabilities, and accordingly refine and improve our model development lifecycle and disseminate best practice learnings to colleagues. Help refine and extend our standards and best practices around Machine Learning – training and testing framework, coding standards, engineering practices. Qualifications & Skills: Demonstrate a strong understanding of natural language processing methods, including deep learning techniques, knowledge distillation, prompt engineering More ❯

Grade Level (for internal use): 12 The Team: The Capital IQ Solutions Data Science team supports the S&P Capital IQ Pro platform with innovative Data Science and Machine Learning solutions, utilizing the most advanced NLP Generative AI models. This role presents a unique opportunity for hands-on ML/NLP/Gen AI/LLM scientists and engineers … to advance to the next step in their career journey and apply their technical expertise in NLP, deep learning, Gen AI, and LLMs to drive business value for multiple stakeholders while conducting cutting-edge applied research in LLMs, Gen AI, and related areas. Responsibilities and Impact: Develop models, algorithms and data pipelines that leverage wealth of S&P … subjects Requirements and Skills Master's or Ph.D. in Data Science, Statistics, Mathematics, Computer Science, or a related field. 6+ years of professional experience in Data Science/Machine Learning/Quant, including in the Financial Services sector Hands on project lifecycle experience, from business requirements gathering to testing production release Strong coding experience in Python to write robust More ❯

team collaborating with business stakeholders, technology teams, and other relevant groups to understand their needs, gather requirements, and align AI solutions with organisational goals. Prototyping, developing, and deploying machine learning applications into production Contributing to our machine learning enabled, business-facing applications Contributing effective, high quality code to our codebase Model validation and model testing of production models … Presenting findings to senior internal and external stakeholders in written reports and presentations. This role is for you if: Python for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow) Understanding of machine learning techniques Experience with data manipulation libraries (e.g. Pandas, Spark, SQL) Problem … Architecture, Incident Management and Resolution (IMR), Inclusion, Information and Communications Technology (ICT), Intellectual Curiosity, IT Infrastructure Upgrades, IT Operations, IT Operations Management, IT Project Lifecycle, IT Support, IT Troubleshooting, Learning Agility {+ 11 more} Desired Languages (If blank, desired languages not specified) Travel Requirements Not Specified Available for Work Visa Sponsorship? Yes Government Clearance Required? No Job Posting End More ❯

Strong proficiency in programming languages such as Python or R. Experience with SQL and familiarity with database management practices to handle and query large datasets efficiently. Knowledge of machine learning frameworks like TensorFlow or PyTorch and libraries such as scikit-learn. Proficiency in using data analysis and visualization tools to interpret data and present insights effectively. Proven experience as … As the Ideal Candidate, you should have: Analytical Mindset, Curiosity, and Inquisitiveness. Problem-Solving Skills. Attention to Detail. Adaptability and Communication Skills. Patience and Persistence. Experience with advanced machine learning techniques such as deep learning, natural language processing (NLP), or reinforcement learning. Experience in using advanced features of cloud platforms (AWS, Azure, Google Cloud) such as machine … learning services and automated data pipeline tools. Familiarity with big data frameworks like Hadoop or Spark is beneficial. Skills in advanced data visualization tools and software beyond basic reporting—such as Tableau, Power BI, or even more sophisticated interactive web visualization frameworks like D3.js. Benefits 15 Days paid off + local/US Bank holidays. Up to 10% of More ❯

PhysicsX is a deep-tech company of scientists and engineers, developing machine learning applications to massively accelerate physics simulations and enable a new frontier of optimisation opportunities in design and engineering. Born out of numerical physics and proven in Formula One, we help our customers radically improve their concepts and designs, transform their engineering processes and drive operational … wind turbines. We are taking the next leap in building out our technology platform and product offering. In this context, we are looking for a capable and enthusiastic machine learning software engineer to join our research team. If all of this sounds exciting to you, we would love to talk. Note: We are currently recruiting for multiple positions, however … will do Work closely with our research scientists and simulation engineers to build and deliver models that address real-world physics and engineering problems. Design, build and optimise machine learning models with a focus on scalability and efficiency in our application domain. Transform prototype model implementations to robust and optimised implementations. Implement distributed training architectures (e.g., data parallelism, parameter More ❯

their business needs. Your work will range from training next-generation AI cybersecurity firewall LLMs to training foundation genomic models making predictions about life-saving drug proteins. Having a deep curiosity about the hardest questions about LLMs will also motivate various research opportunities on how to apply ML to the forefront of enterprise data. If you are excited about … techniques to integrate tool-calling into production-serving LLMs. Work closely with customers - some of the most sophisticated ML organizations in the world - to quickly prototype and build new deep learning models targeted at multi-modal content understanding problems. Ideally you’d have: At least 1-3 years of model training, deployment and maintenance experience in a production … environment. Strong skills in NLP, LLMs and deep learning. Solid background in algorithms, data structures, and object-oriented programming. Experience working with a cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment. Experience building products with LLMs including knowing the ins and outs of evaluation, experimentation, and designing solutions to get More ❯

their business needs. Your work will range from training next-generation AI cybersecurity firewall LLMs to training foundation genomic models making predictions about life-saving drug proteins. Having a deep curiosity about the hardest questions about LLMs will also motivate various research opportunities on how to apply ML to the forefront of enterprise data. If you are excited about … techniques to integrate tool-calling into production-serving LLMs. Work closely with customers - some of the most sophisticated ML organizations in the world - to quickly prototype and build new deep learning models targeted at multi-modal content understanding problems. Ideally you’d have: At least 1-3 years of model training, deployment and maintenance experience in a production … environment Strong skills in NLP, LLMs and deep learning Solid background in algorithms, data structures, and object-oriented programming Experience working with a cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment Experience building products with LLMs including knowing the ins and outs of evaluation, experimentation, and designing solutions to More ❯