12 of 12 Remote/Hybrid Machine Learning Jobs in West London

/Machine Learning Engineer/Staff Machine Learning/Location: UK (Hybrid or Remote options available) Salary: £60,000 £100,000 per annum (depending on experience) Type: Permanent Recruitment Partner: 167 Solutions Ltd The Opportunity 167 Solutions is working with a forward-thinking organisation that … investing heavily in artificial intelligence and data-driven products. This role sits at the heart of that growth and will suit an AI/Machine Learning Engineer who enjoys taking models from concept through to production. You will work closely with software engineers, data teams, and product stakeholders ...

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: Lead the design and analysis of A/B tests and offline … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced 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, Triton ...

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: Lead the design and analysis of A/B tests and offline … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced 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, Triton ...

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: Lead the design and analysis of A/B tests and offline … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced 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, Triton ...

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: Lead the design and analysis of A/B tests and offline … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced 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, Triton ...

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: Lead the design and analysis of A/B tests and offline … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced 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, Triton ...

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: Lead the design and analysis of A/B tests and offline … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced 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, Triton ...

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: Lead the design and analysis of A/B tests and offline … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced 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, Triton ...

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: Lead the design and analysis of A/B tests and offline … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced 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, Triton ...

Senior Machine Learning Engineer London Are you a Senior ML Engineer who wants to build AI that genuinely matters? Our client is a leading digital technology organisation delivering AI, data, and software solutions to UK public sector and national security customers. They are expanding their machine learning capability and are seeking an experienced engineer to design, evaluate, and deploy production-grade ML and GenAI solutions in high-impact operational environments. What youll be doing: Design and build ML models across forecasting, classification, anomaly detection, and GenAI/LLM use cases Lead experimentation cycles: hypothesis, evaluation, iteration ...

join a high-performing national security team in London, with hybrid working supported. This organisation operates across multiple countries, delivering advanced data, AI and machine learning solutions to government and defence customers in highly complex environments. The Role As a Senior Data Scientist, the focus will … applying cutting-edge AI, machine learning and statistical techniques to real-world national security challenges. The Senior Data Scientist will work across varied projects including exploratory research, bespoke AI solutions and large-scale data platforms, collaborating with technical and non-technical stakeholders. Responsibilities will include shaping projects, delivering ...

these AI solutions to ensure they meet user needs and drive meaningful impact in both healthcare and accessibility domains. Responsibilities: Develop and optimize machine learning models for disease prediction, early diagnosis and personalised healthcare solutions. Process and analyze structured and unstructured health data (EHR, Wearables, HL7/FHIR … implement deep learning algorithms for predictive healthcare applications. Contribute to research on AI-driven personalization strategies to empower users in managing their health effectively. Develop AI-powered accessibility solutions for our products, leveraging multi-modal AI (text, image, audio). Adhere to data privacy regulations (GDPR, MDR, HIPPA, EHDS ...