1 to 25 of 4,423 Machine Learning Jobs in England

environment. Ability to write clean, scalable, robust code using python or similar programming languages. Background in software engineering a plus. Knowledge of data governance frameworks and practices. Understanding of machine learning workflows and how to support them with robust data pipelines. DESIRABLE LANGUAGES/TOOLS Proficiency in programming languages such as Python, Java, Scala, or SQL for data More ❯

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. Implement automated data … 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 … and collaboration skills in cross-functional teams . Preferred Skills High-Performance Computing (HPC) and AI workloads for large-scale enterprise solutions. NVIDIA CUDA, cuDNN, TensorRT experience for deep learning acceleration. Big Data platforms (Hadoop, Spark) for AI-driven analytics in professional services. Pls share CV at [email protected] More ❯

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. Implement automated data … 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 … and collaboration skills in cross-functional teams . Preferred Skills High-Performance Computing (HPC) and AI workloads for large-scale enterprise solutions. NVIDIA CUDA, cuDNN, TensorRT experience for deep learning acceleration. Big Data platforms (Hadoop, Spark) for AI-driven analytics in professional services. Pls share CV at [email protected] More ❯

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. Implement automated data … 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 … and collaboration skills in cross-functional teams . Preferred Skills High-Performance Computing (HPC) and AI workloads for large-scale enterprise solutions. NVIDIA CUDA, cuDNN, TensorRT experience for deep learning acceleration. Big Data platforms (Hadoop, Spark) for AI-driven analytics in professional services. Pls share CV at [email protected] More ❯

Job Description Salary- 90k-100k, plus 25k bonus Role Overview As Head of AI, you will be the primary technical driver of all AI/ML initiatives. You’ll report directly to the CEO/CTO and own the full lifecycle of our AI roadmap—from research and proof-of-concept to scalable production. We’re looking for a “doer … integrate AI features into our platform. • Continuously evaluate new research, open-source tools, and emerging frameworks to keep us at the forefront. • Recruit, mentor, and grow an AI/ML team as we scale beyond our seed round. ⸻ Key Responsibilities 1. Architecture & Hands-On Development • Define and implement end-to-end AI pipelines: data collection/cleaning, feature engineering, model … and maintenance of scalable data pipelines (ETL/ELT) and data lakes/warehouses. • Establish best practices for data labeling, versioning, and governance to ensure high data quality. • Implement ML Ops processes: CI/CD for model training, automated testing, model–drift detection, and continuous monitoring. 4. Team Building & Mentorship • Hire and mentor AI/ML engineers, data scientists, and More ❯

Hands-on Machine Learning Operations (MLOps) Lead. This role will be pivotal in building out a greenfield framework for the deployment and management of scalable AI/ML solutions, specifically for the front and Middle Office user base. The role is to define and set up a greenfield standardized MLOps framework for capital markets and set up all … for Capital markets. The core platform is built on Azure Databricks Lakehouse, consolidating data from various front and Middle Office systems to support BI, MI, and advanced AI/ML analytics. As a lead, you will shape the MLOps framework and establish best practices for deploying and managing AI/ML solutions for a diverse and dynamic user base, including … data scientists, quants, risk managers, traders, and other tech-savvy users. Core Responsibilities: Lead the development of AI/ML CI/CD pipelines and frameworks for supporting AI/ML and Data Science solutions on Azure Databricks. Define and implement best practices for DataOps, DevOps, ModelOps, and LLMOps to standardize and accelerate the AI/ML life cycle. Collaborate More ❯

continuous years, and unspent criminal record check (known as Disclosure and Barring Service) Your Role We are looking for people with strong technical knowledge in areas such as machine learning, GenAI, computer vision, and data science, combined with solid solution architecture and software engineering skills, that will allow us to design and build solutions which can be deployed … your working reality. We have built an inclusive and welcoming environment, for everyone. Your Skills and Experience Capabilities in a range of AI techniques (e.g. supervised and un-supervised machine learning techniques, GenAI, deep learning, graph data analytics, statistical analysis, time series, geospatial, NLP, sentiment analysis, pattern detection, etc.). Strong communication skills - able to compellingly present … organisations, through e.g. the RFI/RFP process, as preferred bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms - demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools More ❯

with the Technical Agent for Data Strategy to implement the Data Analytics/AI and Technology strategy for the Agency Network. Lead advanced research and experimentation in AI, including Machine Learning and Generative AI, and statistical modelling Develop and implement complex data science solutions, ensuring they deliver measurable business improvements. This will include the development of AI solutions … criteria Experience and knowledge of Cloudera Data Platform. Change management experience. An appreciation of the Bank's approach to monetary and/or financial policy, with an interest in learning more about how Agency intelligence and data informs this This is a people management role. You will be responsible for day to day management of the team and for More ❯

products and automations specifically within a performance media context. This includes hands-on experience with campaign optimization, bidding algorithms, audience segmentation, and reporting solutions• Deep understanding of AI/ML concepts and techniques, with practical experience in applying them to real-world marketing challenges• Experience building products and automations leveraging Large Language Models (LLMs) and AI agent frameworks• Familiarity and … ability to identify innovative AI solutions and successfully scale them within an organization• Strong coding skills in Python or similar languages, with experience in developing and deploying AI/ML models• Proficiency in working with data and analytics platforms, including experience with data manipulation, analysis, and visualization• Excellent analytical and problem-solving skills, with the ability to translate complex data More ❯

to clearly communicate complex technicalities to any audience A passionate drive for code quality & results About the Role We are seeking a highly skilled and experienced Senior AI/ML Engineer to join our growing data science team in London (we are 5 at the moment), who is especially passionate about software engineering of the Data science solutions. In this … selecting, filtering, aggregating, and joining data using core clauses, use of CTEs, window functions, subqueries, and data cleaning functions to handle more complex analytical queries Implementation of the foundational ML algorithms, classic NLP techniques, LLM in Python applications More ❯

renowned brands including William Hill, 888, and Mr Green and we're looking for an experienced (London or Leeds based) Data Scientist to be responsible for developing AI/ML methods, processes and systems to extract knowledge or insights to drive the future of artificial intelligence. What you will be doing: Applying and/or developing statistical modelling techniques (such … as deep neural networks, Bayesian models, Generative AI, Forecasting), optimization methods and other ML techniques Converting data into practical insights Analysing and investigating data quality for identified data and communicate it to Product Owner, Business Analyst, and other relevant stakeholders Collecting Data, exploring it, and performing analysis to extract information suitable to the business need. You will identify gaps in … sources with excellent coding skills in Python, R, SQL etc. Understanding of cloud services AWS, Snowflake and Databricks. Evidence of academic training in Statistics. Deep/broad knowledge of machine learning, statistics, optimisation, or related field with exposure to Generative AI and Large Language Models. A genuine curiosity about new and applied technology and software engineering coupled with More ❯

opportunity to help provide crucial information and insight to support the management of high-profile health incidents alongside ongoing surveillance activities. UKHSA has a strong data science community with learning opportunities, community groups and hackathon events. We predominantly code in Python and R and utilise AWS and Azure based cloud environments. The teams use Agile ways of working including … strategic and operational decision making use data ethically and appropriately be innovative and adaptable explore existing and new data using a range of statistical tools and techniques, such as machine learning and predictive analytics find patterns in data and transform them into organisational insight Essential Criteria A first or second-class honours degree in a numerate discipline, computer … supporting development of coding capability across the team. Expertise in wrangling, cleaning and preprocessing data for readiness for analysis and guiding best practice across the team. Ability to apply machine learning techniques, critically assessing model performance, limitations and ethical considerations whilst supporting the development of best practice across the team. Previous experience of leading a team of data More ❯

ideas are recognised and contribute to the success of the team and the organisation. Be Empowered: Start with a structured Early Careers Induction Programme, access 24/7 e-learning, and gain professional certifications to sharpen your expertise. Be Collaborative: Our Student Kick-start Initiative will give you the chance to work with fellow graduates on creative and impactful … Languages C++ Java Python JavaScript C# Systems & Tools Linux/Unix operating systems Cloud Technologies (AWS, Azure, Google Cloud) DevOps tools (e.g., Docker, Kubernetes) Version Control Systems (e.g., Git) Machine Learning/AI technologies Software Development Understanding of software development methodologies, including Agile and DevOps practices. Networking & Cybersecurity Familiarity with networking protocols, firewalls, VPNs, and cybersecurity practices is More ❯

present solutions Strong project management skills with ability to balance multiple priorities and deliver on time Collaborative mindset with experience working in cross-functional teams Bonus Points Experience with machine learning workflows and MLOps practices Knowledge of real-time streaming data processing (Kafka, Kinesis) Background in consulting or client-facing technical roles Contributions to open-source analytics or More ❯

database design and performance optimization. Experience with industry standard frameworks and tools such as SpringBoot, DropWizard, Maven, Web/RESTful service development, etc. Knowledge of ORM frameworks. Experience in ML/Data Science/AWS will be relevant and useful. Experience with continuous delivery and deployment. Proficient at working with large and complex code bases. Sound in object-oriented programming More ❯

database design and performance optimization. Experience with industry standard frameworks and tools such as SpringBoot, DropWizard, Maven, Web/RESTful service development, etc. Knowledge of ORM frameworks. Experience in ML/Data Science/AWS will be relevant and useful. Experience with continuous delivery and deployment. Proficient at working with large and complex code bases. Sound in object-oriented programming More ❯

database design and performance optimization. Experience with industry standard frameworks and tools such as SpringBoot, DropWizard, Maven, Web/RESTful service development, etc. Knowledge of ORM frameworks. Experience in ML/Data Science/AWS will be relevant and useful. Experience with continuous delivery and deployment. Proficient at working with large and complex code bases. Sound in object-oriented programming More ❯

warehouses, create the processes to extract or access operational data, and transform siloed datasets into integrated data models that allow insight into business performance and problems or training of ML models. These are hands-on, client-facing roles, with openings at senior or lead level to suit your experience. You may be leading teams, setting technical direction, advising clients or More ❯

computing platforms. You will work closely with data scientists and software engineers to streamline the deployment and monitoring of machine learning models, ensuring efficiency and reliability in ML operations. We hire based on personality, potential, and enthusiasm to make a difference, then we give you the tools and skills you need to follow your own path. You'll … into practice and become certified on various Cloud (and related) technologies that will help you to develop your own toolkit. Requirements Software Engineering: Proficiency in programming languages used in ML, such as Python/Java. Knowledge of software development best practices and methodologies. Experience with version control systems (e.g., Git). Familiarity with CI/CD tools and practices. Strong … analytical skills. Understanding of data structures and algorithms. Ability to design and develop scalable, efficient, and maintainable software systems. Experience with microservice architecture, API development. Machine Learning (ML): Deep understanding of machine learning principles, algorithms, and techniques. Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. Proficiency in data preprocessing More ❯

computing platforms. You will work closely with data scientists and software engineers to streamline the deployment and monitoring of machine learning models, ensuring efficiency and reliability in ML operations. We hire based on personality, potential, and enthusiasm to make a difference, then we give you the tools and skills you need to follow your own path. You'll … into practice and become certified on various Cloud (and related) technologies that will help you to develop your own toolkit. Requirements Software Engineering: • Proficiency in programming languages used in ML, such as Python/Java. • Knowledge of software development best practices and methodologies. • Experience with version control systems (e.g., Git). • Familiarity with CI/CD tools and practices. • Strong … analytical skills. • Understanding of data structures and algorithms. • Ability to design and develop scalable, efficient, and maintainable software systems. • Experience with microservice architecture, API development. Machine Learning (ML): • Deep understanding of machine learning principles, algorithms, and techniques. • Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. • Proficiency in data preprocessing More ❯

and AWS that enable real-time data-driven decision-making Work closely with the Director of Data Science and cross-functional teams to identify data requirements, define data and ML models, and develop scalable solutions to support our growing data needs Build, maintain and monitor data products that ensure data quality, accuracy, and availability Continuously monitor and evaluate data infrastructure … and exceptional conditions in the data Knowledge working with structured and unstructured data formats Experience designing and implementing data pipelines and ETL processes is a plus Good knowledge of ML ops principles and best practices to deploy, monitor and maintain machine learning models in production Familiarity with Git and MLflow for managing and tracking model versions Experience with … with container technologies (such as Docker) and orchestration technologies (such as Kubernetes) Experience working in ecommerce or retail industries is a plus An understanding of security measures related to ML models ensuring adherence to data privacy regulations YOU (BEHAVIOURAL SKILLS) Excellent problem-solving and analytical skills, with the ability to identify and resolve complex data infrastructure issues Proficient collaborating with More ❯

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 … 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-world challenges such as intelligence extraction and inference Productize, develop, optimize and deploy ML and NLP algorithms, supportive modules (such as architects, data processors … with cloud platforms such as AWS, Azure, Google Cloud Platform Experience with research communities and/or efforts, including having published papers (being listed as author) at AI/ML/NLP/CV conferences (e.g. NeuraIPS, ICML, ICLR, ACL, EMNLP, NAACL, CVPR, KDD, etc.) and biomedical journals Perks and Benefits Salary depending on experience. Benefits include private medical insurance More ❯

evaluation, performance tuning, and A/B testing methodologies Continuously monitor model behaviour post-deployment, addressing drift, feedback loops, and retraining strategies Contribute to and influence architectural decisions regarding ML systems and tooling (e.g., feature stores, orchestration frameworks, vector databases) Lead technical discussions, code reviews, and mentoring sessions for junior and mid-level data scientists Lead R&D initiatives by … all the skills, you have a passion and willingness for learning. Here’s what the teams will be looking for: 5+ years hands on experience in data science or ML role with a strong focus on building and deploying production systems Deep technical expertise in machine learning, including supervised/unsupervised learning, NLP, and/or deep … learning Experience with large language models (LLMs), transformers, and modern NLP techniques (e.g., fine-tuning, embeddings, prompt engineering) Proven track record in designing, scaling, and maintaining ML systems in production (cloud-native solutions preferred – e.g., Azure, AWS, GCP) Excellent problem-solving skills and a passion for innovation and continuous learning Strong Python programming skills to write clean, modular More ❯

evaluation, performance tuning, and A/B testing methodologies Continuously monitor model behaviour post-deployment, addressing drift, feedback loops, and retraining strategies Contribute to and influence architectural decisions regarding ML systems and tooling (e.g., feature stores, orchestration frameworks, vector databases) Lead technical discussions, code reviews, and mentoring sessions for junior and mid-level data scientists Lead R&D initiatives by … all the skills, you have a passion and willingness for learning. Here’s what the teams will be looking for: 5+ years hands on experience in data science or ML role with a strong focus on building and deploying production systems Deep technical expertise in machine learning, including supervised/unsupervised learning, NLP, and/or deep … learning Experience with large language models (LLMs), transformers, and modern NLP techniques (e.g., fine-tuning, embeddings, prompt engineering) Proven track record in designing, scaling, and maintaining ML systems in production (cloud-native solutions preferred – e.g., Azure, AWS, GCP) Excellent problem-solving skills and a passion for innovation and continuous learning Strong Python programming skills to write clean, modular More ❯

evaluation, performance tuning, and A/B testing methodologies Continuously monitor model behaviour post-deployment, addressing drift, feedback loops, and retraining strategies Contribute to and influence architectural decisions regarding ML systems and tooling (e.g., feature stores, orchestration frameworks, vector databases) Lead technical discussions, code reviews, and mentoring sessions for junior and mid-level data scientists Lead R&D initiatives by … all the skills, you have a passion and willingness for learning. Here’s what the teams will be looking for: 5+ years hands on experience in data science or ML role with a strong focus on building and deploying production systems Deep technical expertise in machine learning, including supervised/unsupervised learning, NLP, and/or deep … learning Experience with large language models (LLMs), transformers, and modern NLP techniques (e.g., fine-tuning, embeddings, prompt engineering) Proven track record in designing, scaling, and maintaining ML systems in production (cloud-native solutions preferred – e.g., Azure, AWS, GCP) Excellent problem-solving skills and a passion for innovation and continuous learning Strong Python programming skills to write clean, modular More ❯