1 to 25 of 54 Machine Learning Jobs in Kent

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 ...

semi-autonomous agents using modern agent frameworks and Google AI tooling. Collaborate with product and engineering teams to translate complex business requirements into ML-driven solutions. Monitor, optimise, and continuously improve models in live production environments. Contribute to the architecture and evolution of the AI platform and supporting data infrastructure. … Stay current with emerging research, tools, and best practices across ML and Generative AI. What We're Looking For Essential 5+ years' experience in machine learning engineering or applied AI roles. Recent, demonstrable experience with LLMs, Generative AI, and/or RAG-based systems. Strong Python skills using ...

semi-autonomous agents using modern agent frameworks and Google AI tooling. Collaborate with product and engineering teams to translate complex business requirements into ML-driven solutions. Monitor, optimise, and continuously improve models in live production environments. Contribute to the architecture and evolution of the AI platform and supporting data infrastructure. … Stay current with emerging research, tools, and best practices across ML and Generative AI. What We're Looking For Essential 5+ years' experience in machine learning engineering or applied AI roles. Recent, demonstrable experience with LLMs, Generative AI, and/or RAG-based systems. Strong Python skills using ...

Role Summary We are seeking a creative and skilled AI Engineer to help drive Unlinks mission of transforming justice services through advanced AI and machine learning. You will work on meaningful, high-impact projects—like predictive analytics for offender risk, behavioural monitoring, secure communications enhancement, and operational optimization—ensuring … nature of justice services. Person Specification Must-Have: Degree in Computer Science, AI, Data Science, or equivalent experience. Strong Python skills, with experience in ML libraries like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure ...

Role Summary We are seeking a creative and skilled AI Engineer to help drive Unlinks mission of transforming justice services through advanced AI and machine learning. You will work on meaningful, high-impact projects—like predictive analytics for offender risk, behavioural monitoring, secure communications enhancement, and operational optimization—ensuring … nature of justice services. Person Specification Must-Have: Degree in Computer Science, AI, Data Science, or equivalent experience. Strong Python skills, with experience in ML libraries like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure ...

MLOps workflows. · Work across internal products and contract-based venture projects. Requirements · Strong foundational programming skills in Python. · Basic understanding of AI/ML models and how they are trained, deployed, and run. · Familiarity/understanding with version control software (git). · Ability to work in a fast-moving environment ...

MLOps workflows. · Work across internal products and contract-based venture projects. Requirements · Strong foundational programming skills in Python. · Basic understanding of AI/ML models and how they are trained, deployed, and run. · Familiarity/understanding with version control software (git). · Ability to work in a fast-moving environment ...

.To be successful, you must have , experience of regulated environments, the ability challenge senior stake holders within model and analytics risk, including AI/ML bias, drift, explainability, and responsible use and strong knowledge of 2nd or 3rd line experience (1st line would not be considered). Core responsibilities: Provide ...

Data+ certification and enables you to demonstrate your knowledge in advanced data processing, cleaning, and statistical modelling concepts. You will demonstrate your knowledge of machine learning, industry trends and use of specialised data science applications. You will also apply mathematical and statistical methods appropriately. Step ...

modern AI ecosystems including generative AI, agentic systems, AI copilots, and orchestration frameworks (e.g. LangChain, AutoGen, CrewAI). Understands how to combine traditional ML and analytics with emerging AI architectures to deliver measurable commercial value. Evolved beyond a purely data science or analytics focus — can bridge data foundations with GenAI ...

modern AI ecosystems including generative AI, agentic systems, AI copilots, and orchestration frameworks (e.g. LangChain, AutoGen, CrewAI). Understands how to combine traditional ML and analytics with emerging AI architectures to deliver measurable commercial value. Evolved beyond a purely data science or analytics focus — can bridge data foundations with GenAI ...

modern AI ecosystems including generative AI, agentic systems, AI copilots, and orchestration frameworks (e.g. LangChain, AutoGen, CrewAI). Understands how to combine traditional ML and analytics with emerging AI architectures to deliver measurable commercial value. Evolved beyond a purely data science or analytics focus — can bridge data foundations with GenAI ...

modern AI ecosystems including generative AI, agentic systems, AI copilots, and orchestration frameworks (e.g. LangChain, AutoGen, CrewAI). Understands how to combine traditional ML and analytics with emerging AI architectures to deliver measurable commercial value. Evolved beyond a purely data science or analytics focus — can bridge data foundations with GenAI ...

modern AI ecosystems including generative AI, agentic systems, AI copilots, and orchestration frameworks (e.g. LangChain, AutoGen, CrewAI). Understands how to combine traditional ML and analytics with emerging AI architectures to deliver measurable commercial value. Evolved beyond a purely data science or analytics focus — can bridge data foundations with GenAI ...

modern AI ecosystems including generative AI, agentic systems, AI copilots, and orchestration frameworks (e.g. LangChain, AutoGen, CrewAI). Understands how to combine traditional ML and analytics with emerging AI architectures to deliver measurable commercial value. Evolved beyond a purely data science or analytics focus — can bridge data foundations with GenAI ...

guidance to junior engineers. Collaborate with product and engineering teams to integrate AI functionality into the platform. Required Experience Experience as an AI or Machine Learning Engineer with responsibility for end-to-end model development and deployment. Deep knowledge of RAG Experience processing high volumens of documentation/… leading technical initiatives. Nice to Have Experience working with sensitive or regulated data (not essential). Experience with graph-based retrieval. Familiarity with Azure ML or similar tooling. Career Path and Growth You will act as the senior figure within the AI group, shaping standards, guiding junior colleagues and influencing ...

guidance to junior engineers. Collaborate with product and engineering teams to integrate AI functionality into the platform. Required Experience Experience as an AI or Machine Learning Engineer with responsibility for end-to-end model development and deployment. Deep knowledge of RAG Experience processing high volumens of documentation/… leading technical initiatives. Nice to Have Experience working with sensitive or regulated data (not essential). Experience with graph-based retrieval. Familiarity with Azure ML or similar tooling. Career Path and Growth You will act as the senior figure within the AI group, shaping standards, guiding junior colleagues and influencing ...

have exceptional coding skills, ideally with Python and/or TypeScript You're genuinely excited about working with LLMs, Computer Vision and Machine Learning You're not afraid of putting in the work; you'll be offered generous equity on top of your salary You consider yourself ...