451 to 475 of 2,178 Machine Learning Jobs in England

ML Ops Engineer - Motion Capture Technology | Hybrid (Oxford, UK) An exciting opportunity has arisen for an ML Ops Engineer to join a world-leading technology company specialising in high-performance motion capture solutions for the entertainment, engineering, and life sciences industries. Their products are widely used in feature films, gaming, commercials, and cutting-edge research in biomechanics, robotics, and beyond. … that's pushing the boundaries of motion capture technology, working in a company with a strong track record of innovation and global impact. The Role: You will join the ML Operations team, supporting the development of next-generation motion capture products. The role involves provisioning and maintaining a modern ML Ops stack, which includes data acquisition pipelines, data management systems … and ML model training infrastructure. This stack combines self-managed on-premises systems with cloud-based AWS resources. As an ML Ops Engineer, you'll have the opportunity to influence technical direction, propose new solutions, and potentially lead projects within the team. The company offers a hybrid working model , with a head office in a major academic city. There is More ❯

Senior Machine Learning Scientist (Generative AI) - Viator London, England About Viator Viator, a Tripadvisor company, is the leading marketplace for travel experiences. We believe that making memories is what travel is all about. And with 300,000+ travel experiences to exploreeverything from simple tours to extreme adventures (and all the niche, interesting stuff in between)making memories that … instruction tuning. Define best practices for model monitoring, including output quality, hallucination detection, and user feedback loops. Understanding use cases for Agentic AI communicating your findings with the wider ML team and product. Utilize RLHF methodologies to build feedback mechanisms that directly shape the behavior and quality of our generative AI outputs. Collaborate cross-functionally with product, design, and engineering … data science experience with at least 2 years of experience with LLM. Awareness of current LLM techniques, prompt tuning, evaluations and model monitoring. In-depth knowledge of AI/ML/DL, Statistics, and related open-source libraries. Strong skills in SQL and at least one programming language. To be comfortable in code reviews, discussing architecture, and collaborating with a More ❯

technology teams, and data scientists, to ensure that final solutions meet requirements. The Lead AI Solutions Engineer is an expert in large language models, Gen AI application implementation and machine learning, and has a passion for creating intelligent systems that automate processes, improve efficiency, and drive business innovation. In this role you will be responsible for: Design and … versioning for AI systems. Mentor and guide junior engineers and cross-functional team members, fostering a culture of technical excellence and collaboration. Stay current with advancements in AI/ML and LLM technologies and proactively identify opportunities to apply them to business challenges. About You: We encourage you to bring your own experience and expertise to the table so, while … to discussing how your individual knowledge might lend itself to fulfilling this role and help us achieve our goals. What you need to have: Proven experience delivering AI/ML solutions in production , with a strong focus on large language models (LLMs) and generative AI. Hands-on expertise with Azure Databricks , including data engineering, model development, and orchestration of ML More ❯

enjoy the journey. Role Overview: Principal AI Engineer You will be part of the Technology Engineering team within CIO, leading the design, development, and deployment of advanced AI and machine learning solutions that drive innovation, efficiency, and strategic value across the organization. Collaborating closely with Data Science, Engineering, Product, and Business teams, you'll understand complex challenges and … data exploration to model deployment and monitoring-ensuring solutions are scalable, ethical, and aligned with enterprise goals. Skills we would love you to have: Extensive experience in AI/ML engineering, data science, or applied machine learning roles. Proven track record of delivering production-grade AI solutions in complex, data-rich environments. Proficiency in Python and key ML … tools. Strong knowledge of data engineering principles, including data wrangling, feature engineering, and pipeline orchestration. Experience with version control (e.g., Git), CI/CD pipelines, and automated testing for ML code. What we offer Join us and experience a different way of doing things-our 4Cs culture focuses on our colleagues, customers, company, and community. We support your growth with More ❯

improve customer engagement. As a Principal AI Engineer, you will be part of the Technology Engineering team within CIO, leading the design, development, and deployment of advanced AI and machine learning solutions that drive innovation, efficiency, and strategic value across the organisation. You will collaborate closely with cross-functional teams, including Data Science, Engineering, Product, and Business stakeholders … exploration to model development, deployment, and monitoring - ensuring solutions are scalable, ethical, and aligned with enterprise goals. Skills we would love you to have: Extensive experience in AI/ML engineering, data science, or applied machine learning roles. Proven track record of delivering production-grade AI solutions in complex, data-rich environments. Proficiency in Python and key ML … code tools. Strong knowledge of data engineering principles, including data wrangling, feature engineering, and pipeline orchestration. Experience with version control (e.g.Git), CI/CD pipelines, and automated testing for ML code. What we offer Join us and you'll find a different way of doing things. We call it the 4Cs. We focus on getting it right for our colleagues More ❯

build and refine machine learning models that deliver genuine commercial impact. What You'll Be Doing: Work closely with fellow data scientists to explore how AI/ML can unlock insights and improve decision-making. Perform advanced analysis on large, complex datasets using statistical and modelling techniques. Build, test, and tune ML models (especially NLP or computer vision … using Python and modern ML libraries, all within Google Cloud Platform (GCP) . Optimise models for accuracy and performance, ready for product integration. Stay up-to-date with the latest developments in data science and AI to drive innovation. Present insights, results, and model performance clearly to both technical and non-technical stakeholders. Ensure your workflows are reproducible and well … documented, including experiment tracking and model lineage. What You'll Bring: 3+ years' experience building and deploying ML models, ideally in NLP or computer vision domains. Expert-level Python and SQL, with solid experience using libraries like Pandas, Scikit-Learn, TensorFlow, etc. Proven experience working with BigQuery and big data pipelines on GCP . Deep understanding of statistics, machine More ❯

build and refine machine learning models that deliver genuine commercial impact. What You'll Be Doing: Work closely with fellow data scientists to explore how AI/ML can unlock insights and improve decision-making. Perform advanced analysis on large, complex datasets using statistical and modelling techniques. Build, test, and tune ML models (especially NLP or computer vision … using Python and modern ML libraries, all within Google Cloud Platform (GCP) . Optimise models for accuracy and performance, ready for product integration. Stay up-to-date with the latest developments in data science and AI to drive innovation. Present insights, results, and model performance clearly to both technical and non-technical stakeholders. Ensure your workflows are reproducible and well … documented, including experiment tracking and model lineage. What You'll Bring: 3+ years' experience building and deploying ML models, ideally in NLP or computer vision domains. Expert-level Python and SQL, with solid experience using libraries like Pandas, Scikit-Learn, TensorFlow, etc. Proven experience working with BigQuery and big data pipelines on GCP . Deep understanding of statistics, machine More ❯

Efficient, fast and cost-effective access to data at large scale is key to tackle the hardest problems in AD/ADAS, from developing the Machine Learning (ML) models for perception and prediction of human driving patterns, to increasing the sophistication of our validation and simulation by identifying rare and interesting real-world driving situations. The data ecosystem … developed by the Data Infrastructure team is a key building block for developing and testing modern AD/ADAS products that will impact millions of customers. Our ML and Data pipelines are built on-top of the open-source Flyte orchestration framework and are deployed to AWS. Pipeline code is written in Python. We leverage AWS S3, GCP BigQuery and … debug/track/resolve by analyzing the root cause of these issues and the impact on users & operations. Work closely with other Data Infrastructure engineers, Site Reliability engineers, ML Platform engineers, Computer Vision and ML engineers on high-impact projects to create innovative solutions to problems in the self-drive space. Mentor junior engineers in their day to day More ❯

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 … challenges into data-driven solutions. Requirements: MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. Strong Python skills (bonus: C++, SQL, Spark) Experience in ML algorithms (XGBoost, clustering, regression) Expertise in Time Series, NLP, Computer Vision, MLOps Knowledge of AWS/Azure/GCP, CI/CD, and Agile development Ability to own solutions and More ❯

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 … challenges into data-driven solutions. Requirements: MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. Strong Python skills (bonus: C++, SQL, Spark) Experience in ML algorithms (XGBoost, clustering, regression) Expertise in Time Series, NLP, Computer Vision, MLOps Knowledge of AWS/Azure/GCP, CI/CD, and Agile development Ability to own solutions and More ❯

the capabilities, team, and infrastructure to unlock high-impact, scalable innovation. What You'll Be Doing Shape Strategy & Lead Innovation Define and deliver the data science vision, spanning GenAI, ML, and advanced analytics. Establish an AI Centre of Excellence to embed a data-first culture across the business. Be the senior voice on AI in leadership forums - shaping how data … science drives strategic value. Build GenAI & ML Solutions Deliver enterprise-scale GenAI apps (e.g. virtual assistants, copilots, RAG systems). Develop robust LLMOps pipelines for scalable AI deployment and governance. Lead classical ML initiatives alongside engineering teams - from training to monitoring. Stay ahead of emerging trends in AI/ML to inform technology adoption. Enable Data-Driven Decision Making Build … using LLMs, prompt engineering, and RAG architectures. Deep understanding of experimentation, statistical modelling, and advanced analytics. Hands-on experience with MLOps practices, cloud environments (AWS or Azure), and classical ML model deployment. Proficiency in Python, SQL, and modern data science tools/platforms. Strong stakeholder engagement skills and the ability to simplify complex insights into strategic recommendations. Bonus Points For More ❯

There is no shortage of enterprise learning management systems on the market. In fact, you could argue that there are a few too many - complicating the process of actually choosing and adopting an LMS. To help smooth out the selection process, CMSWire has taken advice from industry practitioners and experts to figure out what businesses should keep in mind … when choosing an LMS. 1. Define Objectives First things first, you'll want to outline the goals you want to achieve through your future learning management system. Whether that's to improve staff knowledge about your product lines, educate partners or inform the public, you need to know what your objective is in order to plan for it effectively. … Coppa said. "Understand your organization's needs and nuances; your users' needs and experiences; work functions and roles; and required competencies and training needs," he continued. 2. Hunt For ML-Driven and Performance-Based Training Features A great LMS doesn't just present materials to learners. It takes the learner's performance and progress into account to let the company More ❯

NLP, and more to fuel scalable business growth and operational excellence. Role Scope Lead the identification of opportunities and risks in a fast-evolving competitive landscape, using AI/ML to deliver measurable business value & growth. Understand and maintain a RADAR of technologies, in order to understand the risk and reward profile of selecting a technology to capitalise on an … a background in computer science, machine learning, data science or a related STEM field (degree or equivalent experience). Hands-on experience developing and deploying production-grade ML models, including advanced RAG (retrieval-augmented generation) systems. Deep expertise in Generative AI, LLMs, NLP, and Knowledge Graphs-with a track record of translating complex models into real-world business … solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within More ❯

NLP, and more to fuel scalable business growth and operational excellence. Role Scope Lead the identification of opportunities and risks in a fast-evolving competitive landscape, using AI/ML to deliver measurable business value & growth. Understand and maintain a RADAR of technologies, in order to understand the risk and reward profile of selecting a technology to capitalise on an … a background in computer science, machine learning, data science or a related STEM field (degree or equivalent experience). Hands-on experience developing and deploying production-grade ML models, including advanced RAG (retrieval-augmented generation) systems. Deep expertise in Generative AI, LLMs, NLP, and Knowledge Graphs-with a track record of translating complex models into real-world business … solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within More ❯

NLP, and more to fuel scalable business growth and operational excellence. Role Scope Lead the identification of opportunities and risks in a fast-evolving competitive landscape, using AI/ML to deliver measurable business value & growth. Understand and maintain a RADAR of technologies, in order to understand the risk and reward profile of selecting a technology to capitalise on an … a background in computer science, machine learning, data science or a related STEM field (degree or equivalent experience). Hands-on experience developing and deploying production-grade ML models, including advanced RAG (retrieval-augmented generation) systems. Deep expertise in Generative AI, LLMs, NLP, and Knowledge Graphs-with a track record of translating complex models into real-world business … solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within More ❯

NLP, and more to fuel scalable business growth and operational excellence. Role Scope Lead the identification of opportunities and risks in a fast-evolving competitive landscape, using AI/ML to deliver measurable business value & growth. Understand and maintain a RADAR of technologies, in order to understand the risk and reward profile of selecting a technology to capitalise on an … a background in computer science, machine learning, data science or a related STEM field (degree or equivalent experience). Hands-on experience developing and deploying production-grade ML models, including advanced RAG (retrieval-augmented generation) systems. Deep expertise in Generative AI, LLMs, NLP, and Knowledge Graphs-with a track record of translating complex models into real-world business … solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within More ❯

story. We're looking for exceptional talent to join our mission. We offer a chance to create impact in a high-energy and connected culture, while benefiting from continuous learning opportunities, a supportive community which is proud to serve our mission, and comprehensive benefits. Your Team The Customer Risk Monitoring team builds and maintains the analytical intelligence that protects … and batch monitoring capabilities, including: A custom alerting and orchestration platform, built on Airflow, that enables scalable, auditable detection pipelines. Data pipelines in DBT and Snowflake that serve both ML models and rule-based logic. Backend services and APIs that handle case management, automated decisioning, merchant termination workflows, and integrations with adjacent platform services. We collaborate closely with Compliance, Risk … enabling analysts to deploy and manage DAGs safely and effectively. Contribute to the development and maintenance of DBT models and data pipelines integrated with Snowflake to support detection logic, ML models, and investigations. Integrate internal systems with third-party fraud and AML tools, as well as external APIs. Take ownership of features and services throughout their lifecycle, from design through More ❯

creativity to solve our client's challenges! It would be great if you also had experience in some of these, but if not we'll help you with them Machine Learning software e.g. Amazon and Azure machine learning, or Google's TensorFlow Deploying and managing in Cloud Computing such as AWS, MS Azure Containerisation e.g. Docker More ❯

C++ Software Engineers (Numerical Modelling, AI/ML, Python) Guildford, Surrey (On-site)£65000 - £140,000 + 25% Bonus, 10% Pension, Private Medical. - A Masters or PhD Degree in Computing or STEM disciplines.- Can work full-time, 5 days a week in Guildford in the office. Your new company This leading Software provider are looking to bolster their engineering team … the Innovation Team which have a broad mandate to work across the entire suite of internal products. You will contribute to the early-stage exploration of technologies such as Machine Learning and AI Engineering and translate experimental code into production quality implementations in an R&D style environment.You'll be working to deliver a new suite of highly … C++, C#) and at least one high-level scientific language (e.g., Python, Julia) andExperience with scientific computing, numerical methods, or computational modelling.Familiarity with emerging and interdisciplinary technologies such as: machine learning, digital twins, agentic systems, reinforcement learning, probabilistic computing, or control systems. What you'll get in return You'll work for a technology focused company building More ❯

time, 5 days a week in Guildford in the office. Your new company This leading Software provider are looking to bolster their engineering team with an experienced AI/ML Engineer to work on C++ products. You will be working full-time in their head office location in the heart of Guildford close to the University and with excellent transport … to London and the surrounding areas in Surrey. Your new role This role is for someone to design, developing, deploying and integrate scalable, production-grade software and AI/ML systems with existing desktop and web applications. It is not purely an AI/ML role, nor is it a pure coding role - it sits in between the two disciplines … the line. What you'll need to succeed We're looking for 5+ years proficiency working in an R&D environment, with 3 of those directly on AI/ML projects, alongside a Masters or PhD Degree in a STEM or Computing discipline.You must have proven experience working with C++ (ideally integrating ML features into C++ applications), and at least More ❯

owncreativity to solve our client's challenges! It would be great if you also had experience in some of these, but if not we'll help you with them Machine Learning softwaree.g. Amazon and Azure machine learning, or Google'sTensorFlow Deploying and managing in Cloud Computing such as AWS, MS Azure Containerisation e.g. Docker, Kubernetes Relational More ❯

owncreativity to solve our client's challenges! It would be great if you also had experience in some of these, but if not we'll help you with them Machine Learning softwaree.g. Amazon and Azure machine learning, or Google'sTensorFlow Deploying and managing in Cloud Computing such as AWS, MS Azure Containerisation e.g. Docker, Kubernetes Relational More ❯

helping global brands design and deploy intelligent systems that solve real business problems. They combine deep engineering know-how with domain expertise to build the data infrastructure that powers machine learning and generative AI at scale. 🔍 About the Role As a Lead Data Engineer , you’ll play a critical role in delivering AI-driven solutions for clients—owning … ensure clean, accessible, and production-grade data pipelines are in place to support experimentation and deployment. 🛠️ Key Responsibilities Build and maintain high-performance data pipelines to power AI/ML use cases Architect cloud-native data platforms using tools like Databricks , Airflow , Snowflake , and Spark Collaborate with AI/ML teams to align data processing with model requirements Develop ETL … GDPR , RBAC) Mentor junior engineers and guide technical decisions on client engagements ✅ Ideal Experience Strong in Python and SQL , plus familiarity with Scala or Java Experience supporting AI/ML workflows and working with Data Scientists Exposure to cloud platforms: AWS , Azure , or GCP Hands-on with modern data tooling: Spark , Databricks , Snowflake , Airflow Solid grasp of data modelling, orchestration More ❯

helping global brands design and deploy intelligent systems that solve real business problems. They combine deep engineering know-how with domain expertise to build the data infrastructure that powers machine learning and generative AI at scale. 🔍 About the Role As a Lead Data Engineer , you’ll play a critical role in delivering AI-driven solutions for clients—owning … ensure clean, accessible, and production-grade data pipelines are in place to support experimentation and deployment. 🛠️ Key Responsibilities Build and maintain high-performance data pipelines to power AI/ML use cases Architect cloud-native data platforms using tools like Databricks , Airflow , Snowflake , and Spark Collaborate with AI/ML teams to align data processing with model requirements Develop ETL … GDPR , RBAC) Mentor junior engineers and guide technical decisions on client engagements ✅ Ideal Experience Strong in Python and SQL , plus familiarity with Scala or Java Experience supporting AI/ML workflows and working with Data Scientists Exposure to cloud platforms: AWS , Azure , or GCP Hands-on with modern data tooling: Spark , Databricks , Snowflake , Airflow Solid grasp of data modelling, orchestration More ❯

Role Description We are looking for a machine learning engineer with strong data science expertise to join the team working on large language models for life and natural science problems. Work involves building agentic workflows where LLMs reason, plan and act, as well as developing pipelines to train and fine-tune models. LangGraph is our main … framework for agent development; knowledge of other agent stacks is a plus Key Responsibilities Design and build multi-step LLM agents with LangGraph and similar frameworks Create data and ML pipelines for continual pre-training, supervised fine-tuning and RL alignment Deploy models and retrieval services on containerised infrastructure with reliable CI/CD Monitor and improve agent performance with … Python skills with PyTorch, HuggingFace Transformers and Datasets Proven track record fine-tuning and serving large language models in real-world settings Hands-on experience building pipelines with reinforcement-learning algorithms such as PPO and GRPO Competence with containers, automated testing and software-engineering best practice Useful Skills Basic experience with GCP and infrastructure-as-code workflows Hands-on More ❯