101 to 125 of 194 Deep Learning Jobs in the UK

London The Data Science function plays a pivotal role in delivering advanced Artificial Intelligence capabilities across the organisation. This position focuses on designing, developing, and deploying production-grade machine learning solutions while contributing to the strategic growth of AI-driven products. The successful candidate will join a multidisciplinary, globally distributed team and collaborate closely with Software Engineers, Product Managers … and other stakeholders. The role requires strong mathematical and statistical foundations, excellent software engineering skills, and proven expertise in modern machine learning techniques, including Computer Vision, Natural Language Processing, and Deep Learning. ---------------------------------------- Key Responsibilities Design, build, and deploy advanced machine learning models and algorithms into production. Lead technical development within cross-functional teams, providing guidance on ML … Models (LLMs). Demonstrated success delivering Computer Vision and/or NLP/LLM projects into production. Solid understanding of model deployment, pipelines, and software development fundamentals. Expertise in Deep Learning, including training, evaluation, and optimisation. Strong grounding in mathematics, statistics, and data analysis. Experience working in Agile environments. Familiarity with technologies such as AWS, GCP, Kubernetes, Ray More ❯

clients across the UK and internationally make healthcare more transparent and efficient.You’ll be part of a small, agile team where your work will have real impact and where learning and growth are built into the culture. Whether it’s expanding your technical toolkit or getting closer to the business side of data, this role is designed to help … across teams to improve data workflows and infrastructure What You’ll Bring Solid Python and SQL skills Clear verbal and written communication A genuine interest in AI, LLMs, machine learning, and deep learning — if you’ve worked with them, great; if not, you’ll be supported to learn This is more than just a job it’s More ❯

/ML instrumentation to extract insights and optimize the product experience. Provide strategic product guidance through data-driven recommendations, experimentation insights, and root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and … up to date with industry advancements in data processing and AI/ML, and introduce best practices into the organization. Requirements 7+ years of experience in data science, machine learning, and AI development across structured and unstructured data. Advanced degree (Master’s or PhD) in Computer Science, Engineering, Mathematics, Statistics, or a related field (preferred) Deep experience in … personalization, search, or recommendation systems (3–4 years in a product-focused environment). Expertise in deep learning architectures (e.g., attention models, transformers, retrieval models). Hands-on experience with LLMs and GenAI technologies. Strong programming and problem-solving skills with proficiency in Python, SQL, Spark, and Hive. Deep understanding of classical and modern ML techniques, A More ❯

/ML instrumentation to extract insights and optimize the product experience. Provide strategic product guidance through data-driven recommendations, experimentation insights, and root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and … up to date with industry advancements in data processing and AI/ML, and introduce best practices into the organization. Requirements 7+ years of experience in data science, machine learning, and AI development across structured and unstructured data. Advanced degree (Master’s or PhD) in Computer Science, Engineering, Mathematics, Statistics, or a related field (preferred) Deep experience in … personalization, search, or recommendation systems (3–4 years in a product-focused environment). Expertise in deep learning architectures (e.g., attention models, transformers, retrieval models). Hands-on experience with LLMs and GenAI technologies. Strong programming and problem-solving skills with proficiency in Python, SQL, Spark, and Hive. Deep understanding of classical and modern ML techniques, A More ❯

Overview Postgraduate study in AI and Machine Learning at UCL - scholarships available. UCL Computer Science offers a prestigious education from world renowned experts. Ranked 9th globally (QS World University Rankings 2025) and named The Times and Sunday Times University of the Year 2024, UCL Computer Science provides high quality programmes in AI and ML. With a reputation for leading … UCL Computer Science is ranked first in England and second in the UK for research power in Computer Science and Informatics (REF 2021). Why study AI and Machine Learning at UCL Computer Science UCL is a powerhouse in Artificial Intelligence (AI) and Machine Learning (ML), renowned for shaping some of the field's most important advances and … and humanitarian issues. It offers you an exceptional opportunity to develop solutions for sustainable development, positioning graduates at the forefront of a rapidly growing sector. Computational Statistics and Machine Learning MSc - This one-year MSc combines essential expertise in statistics and machine learning, giving you the skills to excel in an increasingly data driven world. In collaboration with More ❯

regional marketing teams to align with campaign goals Partner with engineering and data teams to ensure scalable solutions Requirements Extensive experience in data science, including applied statistics and machine learning Familiarity with supervised and unsupervised learning, NLP, neural networks, Bayesian statistics, time-series forecasting, collaborative filtering, and deep learning Proficiency in Python and ML libraries (e.g. More ❯

to develop a wide range of new skills on the job. Role Overview: As a Data & ML Engineer, you will design, build, and optimize scalable data pipelines and machine learning solutions. You’ll work with client teams to deliver intelligent data products, leveraging modern cloud and AI technologies. Key Responsibilities Design and implement robust data pipelines and ML workflows … using Python, SQL, Spark, and Databricks. Develop and deploy machine learning models (including NLP, deep learning, and agentic AI) in production environments. Integrate data from diverse sources, including streaming and batch ingestion, using Azure Data Factory, GCP Dataflow and AWS services. Apply data modelling concepts (e.g., medallion architecture) and ensure data quality and governance. Collaborate with DevOps More ❯

Data Scientist, you will be involved in driving insights and strategy for the product team, creating and measuring value through experimentation, creating focus through metrics and goals, and building deep learning about what is most impactful for each team. You will be able to determine the underlying dynamics of our complex ecosystem and use this to deliver insights … at Trainline exists within the wider data organisation as part of the tech org, and is complemented by data engineering teams, data platform teams, and ML teams for when deep ML and AI techniques are required. Our autonomous model creates a huge opportunity for personal influence and impact - as the data scientist on the team you will be actively … to develop new technologies/products and is at the forefront of the rail industry, presenting opportunities to launch new products, work to develop product market fit and go deep with techniques like geospatial and graph analyses. With a team of over a hundred technologists delivering daily data driven product releases and platform updates, TPS prioritises scalability, security and More ❯

teams and customer success to deliver measurable outcomes Acting as an internal evangelist for applied data science and innovation 🧠 What You’ll Bring Must-haves Strong understanding of machine learning techniques — clustering, NLP, deep learning Hands-on experience with feature engineering, model evaluation and data exploration Knowledge of modern AI tooling (RAG, fine-tuning, LLMs, agentic frameworks More ❯

Role: Machine Learning Engineer London: Central London - hybrid working Salary: £125,000 + bonus + benefits Industry: Technology Scale Up, circa 300 people The role: You will lead the design & development of robust Machine Learning models to solve complex problems. You will work alongside MLOps to help build the ML infrastructure for these models to be deployed, and … internal stakeholders to ensure the models being built are improving customer experience, and business efficiency. What we're looking for: Experienced ML Engineer, working across LLM, Computer Vision, NLP, Deep Learning Experience with deploying ML models into production An understanding of emerging technologies - such as Retrieval-Augmented Generation (RAG) and Knowledge Graphs A proactive mindset to identify problems More ❯

Role: Machine Learning Engineer London: Central London - hybrid working Salary: £125,000 + bonus + benefits Industry: Technology Scale Up, circa 300 people The role: You will lead the design & development of robust Machine Learning models to solve complex problems. You will work alongside MLOps to help build the ML infrastructure for these models to be deployed, and … internal stakeholders to ensure the models being built are improving customer experience, and business efficiency. What we're looking for: Experienced ML Engineer, working across LLM, Computer Vision, NLP, Deep Learning Experience with deploying ML models into production An understanding of emerging technologies - such as Retrieval-Augmented Generation (RAG) and Knowledge Graphs A proactive mindset to identify problems More ❯

of a 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 deliver machine learning solutions that unlock value and accelerate decision-making. Your work will range from developing and validating robust predictive models for pricing and valuation across diverse asset classes to dynamically … also adopted and delivering measurable business value, supporting deal team members and portfolio company executives. We’re looking for data scientists who are passionate about impact—those who bring deep statistical knowledge, thrive in fast-paced environments, and want to see their models deployed, used, and making a difference. What you will do Build and deliver AI solutions: Design … Establish credibility by delivering high-quality solutions, challenging assumptions constructively, and iterating quickly in response to feedback. Develop broad technical capability: Work across the full data science lifecycle, continuously learning and applying new technologies. Sample project you will work on: Real estate portfolio valuation: Work on developing advanced valuation models for real estate portfolios using internal and external data More ❯

of a 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 deliver machine learning solutions that unlock value and accelerate decision-making. Your work will range from developing and validating robust predictive models for pricing and valuation across diverse asset classes to dynamically … also adopted and delivering measurable business value, supporting deal team members and portfolio company executives. We’re looking for data scientists who are passionate about impact—those who bring deep statistical knowledge, thrive in fast-paced environments, and want to see their models deployed, used, and making a difference. What you will do Build and deliver AI solutions: Design … Establish credibility by delivering high-quality solutions, challenging assumptions constructively, and iterating quickly in response to feedback. Develop broad technical capability: Work across the full data science lifecycle, continuously learning and applying new technologies. Sample project you will work on: Real estate portfolio valuation: Work on developing advanced valuation models for real estate portfolios using internal and external data More ❯

training. Model Lifecycle Management : Own the full lifecycle — training, evaluation, deployment, monitoring, and retraining. Neural Network Design : Push the boundaries of NLP, computer vision, and recommendation systems with custom deep learning architectures. Enterprise Integration : Embed Gen AI into core business platforms via APIs, microservices, and cloud-native deployments. Responsible AI : Champion ethical, transparent, and bias-aware AI practices … level Python; strong in R, Java, or C++ Hands-on with TensorFlow, PyTorch, Keras, Hugging Face, LangChain Cloud-native mindset: AWS, Azure, GCP + Docker, Kubernetes, CI/CD Deep understanding of ML/DL algorithms, model evaluation, and data engineering Strong communicator and collaborator across technical and business teams Bonus Points Experience with NVIDIA CUDA, cuDNN, TensorRT, and More ❯

Align with our industry partners to develop your career and the solutions we deliver for our clients. In this role you will: Solve challenging business problems using advanced machine learning methods such as Deep Learning and quantitative analytics. Understand business requirements and support the development of business cases. Run discovery analytics to identify new and innovative opportunities. … Partner with developers and engineers to deploy machine learning algorithms to deliver business value. Define approaches to embed and scale machine learning models. Build reusable assets, solutions and develop best practices for current and future business problems. Consult on complex analyses and advanced machine learning methods. Communicate and provide guidance to senior client leadership and teams. Contribute More ❯

for design, development, and support of products, while also leading technical initiatives and contributing to architectural decisions. Domain-Oriented Problem Solving: Go beyond the technical spec to develop a deep empathy for our clients by understanding the nuances of their connected financial data. You will use this domain expertise to contribute to product strategy, challenge assumptions, and architect solutions … problems for our customers, you consistently look to innovate and are not limited by the 'scope' of your role. What you'll bring to the team A broad and deep understanding of a wide range of data science techniques, including classic ML, deep learning and cutting edge AI & Agents, honed through extensive practical experience across a range More ❯

Engineering Manager - Machine Learning | Early-Stage AI Start-Up | London Engineering Manager who has built and managed Machine Learning Engineering or Research teams required to join an early-stage start-up in London building cutting edge AI technology. This is a rare opportunity to join something big from the early days, shape the technical and product direction, and … lead a world-class team developing breakthrough AI systems. About you: Proven experience building and managing ML Engineering and/or Research teams Strong technical background in ML, deep learning, computer vision, or applied AI. Expertise in Python and modern ML frameworks (e.g., PyTorch, TensorFlow) Track record of delivering ML systems in production environments Experience in a start … up or fast-paced, high-ownership environment Excellent leadership, communication, and mentorship skills Bonus points: PhD in Machine Learning, Artificial Intelligence, Computer Science, Applied Mathematics, or a related field. Publications in top-tier journals or conferences (NeurIPS, ICLR, CVPR, ICML) You will: Build, lead and inspire a world class ML team Shape the technology, product, and culture from day More ❯

Engineering Manager - Machine Learning | Early-Stage AI Start-Up | London Engineering Manager who has built and managed Machine Learning Engineering or Research teams required to join an early-stage start-up in London building cutting edge AI technology. This is a rare opportunity to join something big from the early days, shape the technical and product direction, and … lead a world-class team developing breakthrough AI systems. About you: Proven experience building and managing ML Engineering and/or Research teams Strong technical background in ML, deep learning, computer vision, or applied AI. Expertise in Python and modern ML frameworks (e.g., PyTorch, TensorFlow) Track record of delivering ML systems in production environments Experience in a start … up or fast-paced, high-ownership environment Excellent leadership, communication, and mentorship skills Bonus points: PhD in Machine Learning, Artificial Intelligence, Computer Science, Applied Mathematics, or a related field. Publications in top-tier journals or conferences (NeurIPS, ICLR, CVPR, ICML) You will: Build, lead and inspire a world class ML team Shape the technology, product, and culture from day More ❯

that encompasses all aspects of the Traveler’s journey from initial search to final destination. We are seeking a highly skilled data engineer with a strong foundation in Machine Learning (ML) and Artificial Intelligence (AI). This hybrid role is ideal for someone who is passionate about solving complex problems through building scalable global solutions that effectively leverage data … to our customers. Headquartered in Australia, we provide local services solutions to clients across the globe. How You Will Have an Impact Data Engineering/Analytics with a Machine Learning & AI Focus: Design, develop, and deploy ML models and data pipelines to solve business problems. Work with large datasets to build predictive models and insights. Develop Multi-Agent Systems … with effective use of different patterns, hierarchies, and communication protocols. Experiment with different ML techniques, from traditional algorithms to deep learning and reinforcement learning. Make key decisions between the use of LLMs, Transformers, ML algorithms, or simply deterministic software engineering techniques. Optimise model performance, evaluate results, and perform model validation and tuning. Employing credible and justifiable prompt engineering More ❯

business at the forefront of AI innovation in sport and human performance. They’re looking for a Lead AI/ML Engineer to take ownership of their applied machine learning function, with a strong focus on computer vision, automation, and generative AI. This is a hands-on leadership role, ideal for someone who wants to combine technical expertise with … bringing new ideas into production. Partner with domain experts to translate biomechanical data into actionable insights. What we’re looking for Strong background in computer vision and video-based deep learning, (ideally pose estimation, biomechanics or human movement) Proven technical leadership experience, ideally with direct reports. Track record of deploying ML models into production environments. Hands-on skills … with TensorFlow, PyTorch, OpenCV, and Python ML frameworks. Excellent communication skills and ability to work cross-functionally. Desirable MSc/PhD in Machine Learning, Computer Vision, or related field. Knowledge of Generative AI models (GANs, diffusion, LLMs). Experience with MLOps and lifecycle management. Experience in startups or fast-paced R&D. Why apply? Flexible hybrid working (London office More ❯

business at the forefront of AI innovation in sport and human performance. They’re looking for a Lead AI/ML Engineer to take ownership of their applied machine learning function, with a strong focus on computer vision, automation, and generative AI. This is a hands-on leadership role, ideal for someone who wants to combine technical expertise with … bringing new ideas into production. Partner with domain experts to translate biomechanical data into actionable insights. What we’re looking for Strong background in computer vision and video-based deep learning, (ideally pose estimation, biomechanics or human movement) Proven technical leadership experience, ideally with direct reports. Track record of deploying ML models into production environments. Hands-on skills … with TensorFlow, PyTorch, OpenCV, and Python ML frameworks. Excellent communication skills and ability to work cross-functionally. Desirable MSc/PhD in Machine Learning, Computer Vision, or related field. Knowledge of Generative AI models (GANs, diffusion, LLMs). Experience with MLOps and lifecycle management. Experience in startups or fast-paced R&D. Why apply? Flexible hybrid working (London office More ❯

As a Computer Vision and Machine Learning Engineer, you will: Explore and experiment with emerging technologies to continuously improve our AI-driven content reconstruction, creation and edition processes. Review the state of the art computer vision research papers and develop prototype solutions. Develop cutting-edge software and algorithms for computer vision, image processing and deep learning models … Fields (NERF) or Gaussian Splatting techniques. Desirable Skills Demonstrated experience in: Generative AI, including hands-on implementation of state-of-the-art models. 3-D vision Developing with machine learning frameworks – Tensorflow/Pytorch Model optimization and knowledge distillation. Strong fundamentals in machine learning, NLP and Computer Vision Publications in top ML/AI conferences/journals (e.g. More ❯

Contribute to the development of a fantastic visualisation layer for analytics, making complex insights accessible and actionable. Key Skills and Experience NLP Mastery Proficiency in LLMs and transformer architecture. Deep understanding of traditional NLP techniques. Data & Visualisation Solid grasp of data visualisation tools (Tableau, Power BI, Cognos, etc.) Proficiency in Python visualisation libraries (Matplotlib, Seaborn.) SQL for data extraction … datasets. Technical Skills Proficiency in cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling and optimisation. Calculus for optimising algorithms and models. Predictive modelling techniques for regression and classification. Time series … analysis for handling time-dependant data. Deep learning and neural networks. LLM Operations Expertise in managing and operationalising large language models. Experience in deploying models on cloud platforms (e.g. AWS, Sage maker, Google AI Platform, IBM Watson) IND_PC3 More ❯

Contribute to the development of a fantastic visualisation layer for analytics, making complex insights accessible and actionable. Key Skills and Experience NLP Mastery Proficiency in LLMs and transformer architecture. Deep understanding of traditional NLP techniques. Data & Visualisation Solid grasp of data visualisation tools (Tableau, Power BI, Cognos, etc.) Proficiency in Python visualisation libraries (Matplotlib, Seaborn.) SQL for data extraction … datasets. Technical Skills Proficiency in cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling and optimisation. Calculus for optimising algorithms and models. Predictive modelling techniques for regression and classification. Time series … analysis for handling time-dependant data. Deep learning and neural networks. LLM Operations Expertise in managing and operationalising large language models. Experience in deploying models on cloud platforms (e.g. AWS, Sage maker, Google AI Platform, IBM Watson) IND_PC3 More ❯

Machine Learning Engineer (LLM) Transform Language Models into Real-World Applications We're building AI systems for a global audience. We are living in an era of AI transition - this new project team will be focusing on building applications to enable more real world impact and highest usage for the world. This role is a global role with hybrid … and failure as part of growth - you're here to level up. Possess humility, hunger, and hustle, and lift others up as you go. Requirements Strong experience in transformers, deep learning, and fine-tuning methods (LoRA/QLoRA, SFT, distillation). Proficiency with PyTorch (preferred) or TensorFlow. Skilled in prompt engineering and dataset curation for alignment with tone … relevance. Strong software engineering foundations in algorithms, data structures, and clean code practices. Nice to Have Prior work in text generation, moderation, or personalization. Experience with RLHF or reinforcement learning in LLMs. Contributions to open-source ML projects. What You'll Get Flat structure & real ownership Full involvement in direction and consensus decision making Flexibility in work arrangement High More ❯