1 to 25 of 1,392 Machine Learning Jobs in the UK

data infrastructure and machine learning technologies, the company is creating an environment where engineers can work on complex problems, develop scalable ML solutions, and collaborate closely with data scientists, engineers, and product teams. This is an exciting opportunity to join a high-performing team focused on delivering cutting … build, and deploy machine learning models into production environments. You will work closely with data scientists and software engineers to develop scalable ML pipelines, optimise model performance, and integrate machine learning capabilities into production systems. The role involves working with large datasets, building robust ML systems ...

services and deliver value to its clients. Description Machine Learning Engineer - London This role focuses on training custom models, building robust ML pipelines, and deploying systems at scale from research experimentation through to monitored production services. Design, train, and optimise machine learning models for audio processing … tasks such as speaker diarization, automatic speech recognition (ASR), and voice activity detection. Build and maintain training and inference pipelines using PyTorch, and related ML frameworks Source, curate, and prepare training datasets; implement preprocessing, augmentation, and validation workflows. Run structured experiments, evaluate model performance, and iterate based on measurable results ...

Machine Learning Engineer 6 Month Contract UK Based Join us as a Senior Machine Learning Engineer In this role, you'll be driving and embedding the deployment, automation, maintenance and monitoring of machine learning models and algorithms Day-to-day, you'll make sure … problems and enjoy excellent career development What you'll do Your daily responsibilities will include you collaborating with colleagues to design and develop advanced machine learning products which power our group for our customers. You'll also codify and automate complex machine learning model productions, including ...

+ Bonuses & Benefits Location: Cheltenham (3 days on-site per week) Security Clearance: Active Enhanced DV (West) Required Key Skills: Machine Learning, AWS/Azure, Python, NLP, AI Who We Are? We are seeking a highly skilled Data Scientist with enhanced DV clearance to join a globally recognised … techniques to solve complex challenges Conducting research and innovation to develop cutting-edge solutions Keeping up to date with the latest developments in ML and data technologies Engaging in the full data science lifecycle, from data collection to model deployment Producing clear and well-documented technical outputs Delivering high ...

work is thoughtful, challenging, and purposeful, rather than driven by novelty or trend. What you'll be doing You'll take ownership of complex ML problems, applying scientific thinking and pragmatism in equal measure. You will: Lead end-to-end machine learning delivery , from problem definition through experimentation … with internal teams and selected external partners working at the leading edge of AI What we're looking for This role suits a senior ML practitioner who values judgement, evidence, and outcomes over theoretical or tooling purity. Essential experience: Proven experience operating at senior practitioner level as a Machine ...

learning solutions, helping organisations turn complex data into intelligent, real-world outcomes. What you'll have the opportunity to do as a Data & ML Engineer Building and maintaining scalable data pipelines that support analytics and machine learning Developing and deploying machine learning models into production … Supporting good engineering practice across testing, automation and deployment Contributing to Agile delivery through teamwork and continuous improvement About the Candidate The right Data & ML Engineer should have: Experience in data engineering, machine learning or applied AI roles Strong skills in Python and SQL, with exposure ...

work is thoughtful, challenging, and purposeful, rather than driven by novelty or trend. What you'll be doing You'll take ownership of complex ML problems, applying scientific thinking and pragmatism in equal measure. You will: Lead end-to-end machine learning delivery, from problem definition through experimentation … with internal teams and selected external partners working at the leading edge of AI What we're looking for This role suits a senior ML practitioner who values judgement, evidence, and outcomes over theoretical or tooling purity. Essential experience: Proven experience operating at senior practitioner level as a Machine ...

access services quickly and safely. Our Applied Scientist team consists of about twenty machine learning scientists. The team is supported by an ML Ops team that provides state-of-the-art tooling (including AWS, Encord, Ray, PyTorch Lightning and Weights & Biases). The Applied Science team works closely … Have strong experience in machine learning and computer vision. Have a strong record of successfully delivering high-performance ML-driven products. Have a deep understanding of machine learning theory. Have strong coding skills in Python and PyTorch. Care about building fair and cutting-edge machine ...

very excited about our plans for growth over the coming year and beyond! The role We are now looking for a Machine Learning Engineer to build and deliver innovative AI products to our customers. Your software expertise and machine learning knowledge will help transform our customers … challenges and collaborate with them to leverage our AI in the automation of their work. Initially, you will provide hands-on support for our machine learning models as they come to market but then will gradually develop self-service tools that empower customers to achieve value independently. ...

involves collaboration across the UK, Japan and the United States. The Programme Lead will be responsible for overseeing a portfolio of AI and machine learning research initiatives, ensuring that complex research programmes move from experimentation into structured delivery with clear outcomes. This role requires a senior delivery leader … operate comfortably in a highly technical environment, working closely with machine learning engineers, research teams and international stakeholders. The Programme The programme will involve multiple research workstreams focused on emerging areas of artificial intelligence including: • AI privacy and responsible AI frameworks • Development of open source AI platforms • Data ...

deploy machine learning models and pipelines in production environments Collaborate with data scientists, software engineers, and stakeholders to translate business requirements into ML solutions Optimize model performance, scalability, and reliability Build and maintain data pipelines and feature engineering workflows Monitor and retrain models to ensure continued performance over … time Implement best practices for version control, testing, and CI/CD in ML systems Stay up to date with the latest advancements in machine learning and AI technologies Required Skills & Experience Strong programming skills in Python (e.g., TensorFlow, PyTorch, Scikit-learn) Experience deploying ML models using cloud ...

both their technical platform and engineering capability. The Role They are hiring a Senior Machine Learning Engineer to take ownership of their ML strategy and help scale the company’s modelling and data capabilities. This role sits at the core of the business - bridging research, engineering, and product … applied across their discovery pipeline. You’ll be expected to lead from the front: setting technical direction, mentoring engineers, and building production-grade ML systems that integrate closely with biological research workflows. What You’ll Be Doing Lead the design and development of machine learning models applied ...

Machine Learning Engineer (MLOps Python LLM AWS) London/WFH to £90k Are you a senior Machine Learning Engineer looking for an opportunity to take ownership, working on complex and interesting systems? You could be progressing your career in a hands-on technical leadership role … product challenges. You'll define the Machine Learning roadmap from a technical perspective, evaluating model architectures, optimising data pipelines and ensuring that ML features provide actionable insights within the product. This isn't just about training models; it's about building the ML infrastructure that enables the business ...

place to do it. An opportunity to play your part The AI Software Engineer is responsible for designing, building and operating artificial intelligence and machine learning solutions that deliver measurable customer and business value. This role focuses on taking AI from experimentation into production, developing reliable, scalable … using tools such as Python, SQL, Spark or similar data processing technologies. Experience deploying and operating AI systems in cloud environments using containerisation, managed ML services or serverless architectures. Understanding of MLOps practices including model versioning, experiment tracking, CI/CD for models and monitoring of model performance and drift. ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...