9 of 9 Remote/Hybrid Machine Learning Jobs in East London

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 ...

expertise. We’re looking for a mid-senior (4+ years experience) Machine Learning Engineer to help design, build, and scale our production ML systems with ownership from experimentation through to deployment. You’ll work end to end on LLM-powered conversational agents and support the training, optimisation … Offer Train, evaluate and deploy agentic AI systems and computer vision models for real-world use Collaborate with product and engineering to integrate ML systems into user-facing features Develop and deploy production-quality machine learning frameworks, while maintaining robust MLOps pipelines Stay up-to-date with ...

need Strong technical leadership across Azure, AWS, and GCP, with expertise in cloud-native architecture, modernisation, DevOps, automation, containerisation, data platforms and AI/ML solutions. Proven experience leading and growing technical teams within cloud, data, AI and/or application practices. A track record in growing cloud, data ...

data frameworks (DAMA-DMBOK, NIST AI RMF, ISO 23894, ISO 27001, GDPR/DPA 2018); hands-on with platforms such as Microsoft Purview, Azure ML, Databricks, Power BI, Collibra, or Alation; exposure to MLOps practices. ...

sales engineering teams Broad technical foundation across areas such as cloud infrastructure, security and compliance, APIs, integrations, and modern approaches to AI/ML Demonstrated success in supporting large enterprise opportunities, from proof-of-value through to close This company values a top academic history so are looking … Presales Specialist/AI Presales Consultant/SaaS Integrations/APIs/Security/Compliance/AWS/Azure/GCP/NLP/ML/ISO27001/SOC2/GDPR ...