276 to 300 of 4,741 Machine Learning Jobs in the UK excluding London

and stay at the forefront of front-end industry trends, guiding teams on technology adoption. Actively mentor and coach mid-level and junior developers, fostering a culture of continuous learning and skill development. Drive innovation by introducing new methodologies and tools, leading change management initiatives. Foster a highly collaborative team environment, ensuring smooth communication and integration among team members. … you don't tick all of these, we are an organisation that encourages continuous personal development, and are keen to talk with good candidates. Bonus Skills Experience in AI, Machine Learning, or integrating AI models into front-end applications. Familiarity with Python or other languages used in AI development. Experience with cloud platforms (AWS, Azure, GCP). Knowledge More ❯

routines to clean, normalize, and aggregate data. Apply data processing techniques to handle complex data structures, handle missing or inconsistent data, and prepare the data for analysis, reporting, or machine learning tasks. Implement data de-identification/data masking in line with company standards. Monitor data pipelines and data systems to detect and resolve issues promptly. Develop monitoring More ❯

tools and techniques such as SQL, various database types, data formats, and data modelling Demonstrable experience of pipeline logging, usage tracking, and cost monitoring Previous experience deploying analytical/machine learning tools for users Experience leading a team or multiple projects and supporting team members in workload prioritisation and development What you need to do now If you More ❯

related field. Experience in data architecture, engineering, or similar roles. Familiarity with big data technologies, analytics platforms, data fabric, data mesh, and data management technologies. Knowledge of statistical analysis, machine learning, and data visualization. Understanding of microservice architecture, Kubernetes, CI/CD, DevSecOps, and cloud platforms (Azure, AWS, Google Cloud). Experience with electric utilities and industry-specific More ❯

language(s) i.e. Java or Python Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Ability to tackle design and functionality problems independently with little to no oversight Practical cloud native experience Experience in Computer Science, Computer Engineering, Mathematics, or More ❯

keep our firm’s position on the cutting edge. Or, join our core engineering teams, and elevate all of our businesses by providing reliable, scalable platforms for data engineering, machine learning, networking, developer tooling, collaboration, and more. Innovate with UI/UX designers, data scientists, cloud engineers, and more in a collaborative, agile environment where your enthusiasm to More ❯

be able to offer this Site Reliability Engineer role working for an industry-leading software company in Cambridge. This company has won several awards and is pioneering in their machine learning technology. Founded 8 years ago, with a team of 150 brilliant engineers, they are already renowned as having game-changing technology within their industry, with exciting scope More ❯

Understanding of security concepts such as: IAM, Service roles, Encryption, KMS, Secrets Manager Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Experience in Computer Science, Engineering, Mathematics, or a related field and expertise in technology disciplines Exposure to big data frameworks (Spark, Hadoop etc.) used for More ❯

Slack, and TUI trust Matillion technology to load, transform, sync, and orchestrate their data for a wide range of use cases from insights and operational analytics, to data science, machine learning, and AI. With over $300M raised from top Silicon Valley investors, we are on a mission to power the data productivity of our customers and the world. More ❯

transportation. What Makes Us Different: Purpose: you can use your passion and abilities at Leidos to keep the people you care about safe. We are at the forefront of machine learning, AI, cyber security and solutions. Using your skills in the technology frontline by helping to build a safer world. You can inspire change. Collaboration: having flexibility to More ❯

include a strong foundation in the social sciences. Technical expertise Knowledge of Python is required, knowledge of R and SQL is an advantage Experience of techniques such as NLP, machine learning, and LLMs is desirable Experience with tools such as Git and Github, Docker and cloud platforms is highly desirable Policy knowledge: Beyond data science, applicants must have More ❯

in working patterns and a company-wide culture to be proud of. Core skills were looking for to succeed in the role: A strong understanding of Microsoft Azure, (Azure ML, Azure Stream Analytics, Cognitive services, Event Hubs, Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc You … model development, with an emphasis on auditability, versioning, and data security. You'll implement automated data science model testing and validation. You'll assist in the optimisation of deployed ML model scoring code in production services. You'll assist in the design and implementation of data pipelines and engineering infrastructure to embed scaled machine learning solutions. You'll … the wider engineering community. You'll collaborate closely with data scientists, data engineers, architects, and the software development team. You'll liaise with stakeholders across the business to ensure ML is being used to improve strategic business decisions and identify new areas for improvements. You'll adhere to the Group Code of Conduct and Fitness and Propriety policies, Company Policies More ❯

in working patterns and a company-wide culture to be proud of. Core skills were looking for to succeed in the role: A strong understanding of Microsoft Azure, (Azure ML, Azure Stream Analytics, Cognitive services, Event Hubs, Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc You … model development, with an emphasis on auditability, versioning, and data security. You'll implement automated data science model testing and validation. You'll assist in the optimisation of deployed ML model scoring code in production services. You'll assist in the design and implementation of data pipelines and engineering infrastructure to embed scaled machine learning solutions. You'll … the wider engineering community. You'll collaborate closely with data scientists, data engineers, architects, and the software development team. You'll liaise with stakeholders across the business to ensure ML is being used to improve strategic business decisions and identify new areas for improvements. You'll adhere to the Group Code of Conduct and Fitness and Propriety policies, Company Policies More ❯

criteria, monitor impact, and ensure measurable value is delivered at each stage of implementation Required Skills & Experience: Proven experience in solution architecture, with a strong focus on AI/ML or GenAI or Geo-Int implementations across complex environments Hands-on experience delivering AI/GenAI solutions in networks, telecommunications, or customer experience domains is strongly preferred Deep understanding of … Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field Certifications in cloud architecture (e.g., AWS/GCP/Azure Certified Architect), AI/ML, or TOGAF are a plus Familiarity with telco architecture, OSS/BSS systems, or geospatial analytics is an advantage More ❯

and delivering that through the platform. The role will also be responsible for supporting the integrating to system and client APIs and preparing the ground for future AI/ML need in the business. The key differentiator we are looking for is someone who can build a data engineering capability from the ground up and build a team to support … role relate to maintaining and delivering a rolling technology roadmap for data engineering that supports business need and budget targets and preparing the ground then delivering on AI/ML opportunity. Key Accountabilities (major end results the job is expected to achieve): Key Responsibilities: Design, develop, and maintain scalable data pipelines and ETL processes to collect, process, and store large More ❯

AI-compatibility. Enable the use of AI-driven data analytics and business intelligence tools to derive valuable insights from data. Promote data-driven decision-making across the organisation. Operationalise ML, GenAI & RAG - strengthen our LLM-based assistant so colleagues can ask plain-English questions and get clear answers Implement data quality management processes to identify and rectify data errors or … Developing and working with a variety of databases and data sets. Developing/optimising high-volume data pipelines, large datasets and big-data architectures. Deploying or supporting AI/ML workflows. Successfully building processes for transforming data, creating unique data structures to suit end uses, ensuring sufficiency of metadata, and developing methods for automated delivery of data sets (software tools More ❯

data platforms using Dataproc, Dataflow, Pub/Sub, BigQuery, Cloud Spanner, and Bigtable. Define and implement real-time and batch processing pipelines for complex use cases involving streaming analytics, ML feature engineering, and automation. Act as a trusted advisor to senior technical and business stakeholders across industries (e.g., telecom, retail, financial services). Drive data quality, governance, lineage, and security More ❯

TLS, HTTPS, OAuth2, OIDC, SAML, JWT Languages - Python/Node.js/Golang Development – REST API/Microservices Desirable Skills: Multi-Cloud Knowledge/Experience - Azure/AWS. AI/ML – Vertex AI. Engagement with major blue-chip clients/financial organisations Certification GCP Professional Certification – Associate Engineer, Data, DevOps, Developer. More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯

architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support their infrastructure needs, implement DataOps practices, and More ❯