351 to 375 of 1,125 Machine Learning Jobs in England

balance engineering rigor with delivery speed. Solid understanding of software architecture, cloud infrastructure (AWS, Azure, or GCP), and modern DevOps practices. Experience integrating machine learning models into production systems (e.g., LLMs via APIs, fine-tuning, RAG patterns, embeddings, agents … crew of agents etc.). Ability to move quickly while maintaining code quality, test coverage, and operational excellence. Preferred: Familiarity with AI/ML tools such as LangChain, Haystack, Hugging Face, Weaviate, or similar ecosystems. Hands-on experience with Retrieval Augmented Generation applications, AI agents and systems built around them. ...

satisfied Clear and effective communication skills, translating technical concepts for non-technical audiences Thrive in a fast-paced environment with a passion for continuous learning and growth Bonus points for: Proficiency with JavaScript, HTML, and CSS for building front-end applications Knowledge of large ERP systems (SAP, Oracle, Microsoft … Private healthcare/dental Meritocratic working environment and strong career progression opportunities A fast growth, exciting business with an open and inclusive culture Continuous learning and development Great offices and flexible working -- This position is open to candidates eligible to work in the United Kingdom. Sponsorship ...

supported automation and optimisation . Preparing and maintaining high-quality datasets and AI-ready data models (DWH/Lakehouse) to support analytics, reporting, and machine-learning use cases. Monitoring and troubleshooting daily data operations, resolving issues following ITIL best practices, and implementing proactive improvements, alerting, and self-healing … data warehousing, and relational database environments (e.g., MS SQL Server). Experience designing cloud-native and on-prem data solutions. Exposure to AI/ML initiatives , AI-enabled automation, and an understanding of LLM concepts and their data workflow applications. Experience working in Agile environments (Scrum, Kanban, DevOps). Strong ...

clients design, build, and scale modern data platforms. You will play a pivotal role in shaping Lakehouse architectures that enable advanced analytics, AI/ML, and enterprise-wide data-driven decision-making.Working closely with clients early in their data journey, you will assess business needs, define architectural direction, and guide … RBAC, IAM, encryption).* Excellent communication, stakeholder engagement, and problem-solving skills. Highly Valued Certifications* Databricks Certified Data Engineer (Associate/Professional)* Databricks Certified Machine Learning (Associate/Professional)* Databricks Generative AI Fundamentals* Databricks Lakehouse Fundamentals Why Join Us?* Generous annual leave and private medical insurance.* Strong focus ...

communication skills, with the ability to work with both technical and business stakeholders. Useful Certifications (Not Essential) Databricks Data Engineer Associate/Professional Databricks Machine Learning Associate/Professional Databricks Generative AI Fundamentals Databricks Lakehouse Fundamentals What You'll Do Design and implement modern Lakehouse solutions that optimise ...

researchers, and data scientists. The work focuses on building scalable pipelines, enabling real-time analytics, and delivering high-quality datasets used for predictive modelling, machine learning, and systematic trading strategies. This role requires someone who combines strong technical data engineering capability with commercial awareness, capable of working directly ...

Permanent Hybrid Working The Change Partners are working with a global leader in the travel software space to find looking for an ML Engineer to join their Marketing Measurement Analytics team. This is a high-impact role where your code directly influences how brands like global booking platforms allocate investment … 3+ years in a similar role with a globally recognised large brand Production Experience: You’ve built and shipped scalable systems before (ideally with ML/AI components) DevOps Mindset: You’re comfortable with version control, unit testing, and automated deployment pipelines (GitHub Actions). You built reusable frameworks ...

technical roadmap for their AI Platform. Must have strong AI project implementation experience. You will have strong and broad AI concepts, Machine Learning, and Deep Learning technical architecture experience. You will have strong technical solutions design experience. You must also have strong MS Azure and API experience. ...

technical roadmap for their AI Platform. Must have strong AI project implementation experience. You will have strong and broad AI concepts, Machine Learning, and Deep Learning technical architecture experience. You will have strong technical solutions design experience. You must also have strong MS Azure and API experience. ...

technical roadmap for their AI Platform. Must have strong AI project implementation experience. You will have strong and broad AI concepts, Machine Learning, and Deep Learning technical architecture experience. You will have strong technical solutions design experience. You must also have strong MS Azure and API experience. ...

technical roadmap for their AI Platform. Must have strong AI project implementation experience. You will have strong and broad AI concepts, Machine Learning, and Deep Learning technical architecture experience. You will have strong technical solutions design experience. You must also have strong MS Azure and API experience. ...

organisation, which will provide insights into how we operate, and the collaborative environment you’ll be part of. This lays the foundation for a learning journey tailored to your goals and preferred style of development. From day one, you’ll have access to mentors and subject matter experts … encouraged every step of the way, becoming an integral part of our innovative team. We’ll provide the space and resources for continuous learning, experimentation, and improvement – with up to 30% of your time dedicated to personal development. From books, online courses, and conferences to real-world projects supported ...

greenfield product at an early stage Own a core product pillar (audio + AI) from day one Collaborate across embedded, cloud, and ML teams High autonomy in a low-ego, high-performance environment Competitive salary + equity Strong long-term growth and learning opportunities The Role You’ll take … full ownership of the audio subsystem, spanning real-time embedded processing through to cloud-based audio pipelines and ML integration. This role sits between embedded engineering and backend/AI — ideal for someone who enjoys both low-level systems and higher-level software. Key Responsibilities Design and build ...

Snowflake performance, workload management, and cost governance. Establish data governance frameworks including access control, data security, and compliance standards. Design and support AI/ML-ready data architecture for advanced analytics and predictive modelling. Provide architectural guidance to data engineering, BI, and analytics teams. Design architecture to support data consumption … enterprise data modelling Dimensional modelling (Star Schema, Snowflake Schema) Data pipeline scalability and reliability design. AI/Data Science Exposure Experience supporting AI/ML data pipelines and data preparation for machine learning models. Understanding of predictive analytics, recommendation engines, and customer behaviour analytics. Ability to design ...

front-end interfaces using frameworks like Vue.js or React, to present complex datasets and user workflows. • Collaborate with data scientists and engineers to integrate ML models, ETL pipelines, and cloud-based data storage solutions. • Optimise system performance and reliability for high-volume data operations across distributed environments. • Implement secure, compliant … DevOps practices including TDD, CI/CD and infrastructure as code. • Experience of optimising systems for performance and scalability and reliability. • Understanding of machine learning workflows or MLOps for deploying and monitoring models in production. • Experience with cloud platforms, especially AWS and its data services (e.g., BigQuery, Redshift ...

software development activities and support engineering standards for scalable, maintainable codebases Design, build, test and maintain Python-based applications and services Integrate AI/ML components into engineering tooling in collaboration with data scientists and senior engineers Contribute to system and architecture design combining software engineering principles with AI capabilities … software engineering experience, ideally within engineering, industrial or scientific environments Strong hands-on experience developing production-ready applications in Python Exposure to AI/ML technologies or integration of data-driven components into software systems Experience deploying and supporting applications in production Familiarity with cloud platforms, preferably AWS Experience working ...

delivery of complex AI projects across global teams Mentor engineers and data scientists and drive best practice Key requirements Strong background in AI, machine learning or data science Deep experience with LLMs and modern GenAI frameworks Experience designing AI architectures such as RAG and agent-based systems Strong ...

/best practices and practical experience applying TDD. clear communication/interpersonal skills are a must for working closely with internal teams. Experience with Machine Learning, CI/CD and IAC using Terraform for management of Azure/AWS would be beneficial. What you'll get in return ...

Kubernetes. Familiarity with event-driven architecture and message brokers (e.g., Kafka, RabbitMQ). Knowledge of front-end performance optimisation and accessibility standards. Exposure to machine learning pipelines or data engineering workflows. Prior experience working in startup environments or high-growth technology companies. Benefits Hybrid working as standard ...

these processes to link datasets, develop ETL pipelines and identify transactions of potential concern Has an understanding of advanced data science techniques such as machine learning, natural language processing and statistical analysis. Has experience of using data visualisation tools such as PowerBI Has experience with general ledger/ ...

Java/J2EE architectural skills Deep data analytic skills or data scientist. Hands on experience on cutting edge applications of Predictive analytics and Machine learning Hands on experience on development of QA Dashboard with Angular JS, Springboot and MongoDB Create data by utilizing test data tools to setup ...

Scala Experience across Azure, AWS, or GCP ecosystems Nice to Have Exposure to Databricks governance tooling (Unity Catalogue/Purview) Experience with ML/AI workloads on Databricks Knowledge of CI/CD, DevOps, or Infrastructure as Code If you enjoy combining deep technical architecture with commercial influence and client ...

business stakeholders to accelerate value realisation across complex technology estates. Key Responsibilities AI Engineering & Delivery Design, build, and deploy production‐grade AI/ML solutions , including: LLM‐enabled applications (RAG, agents, copilots) Predictive models and intelligent automation AI services embedded into modernised platforms Own end‐to‐end AI lifecycle : discovery ...

financial services Hands-on development: X++, C#, Python, T-SQL, PowerFX, PowerShell Source control and containerization: TFVC, Git, Docker Tools: Azure IPAAS, Azure ML, Dataverse, PowerApps, Power Automate, SQL Server Administration, Fabric, Kafka, Copilot Studio, Azure AI Services, Ollama Integration: REST/SOAP APIs, solution performance analysis Functional knowledge ...

Stats: You must have an excellent grasp of Linear and Logistic Regression . You understand the assumptions, limitations, and interpretability of these models. Advanced ML: Experience with boosting models is essential for our higher-complexity tasks. Analytics Patterns: A core ability to creatively analyse a raw dataset and spot trends ...