1 to 25 of 286 Remote Machine Learning Jobs in the South East

learning models that power data-driven products and business solutions. This role bridges data science and software engineering, focusing on production-ready ML systems, scalability, and performance. The ideal candidate has strong experience in Python, ML frameworks, data pipelines, and cloud platforms, and is comfortable working … unsupervised, and deep learning techniques as appropriate. Perform feature engineering, model tuning, and validation to improve accuracy and performance. 2. Productionisation & Deployment Deploy ML models into production using scalable, reliable architectures. Build and maintain APIs or batch pipelines for model inference. Monitor model performance, data drift, and retraining needs. ...

learning models that power data-driven products and business solutions. This role bridges data science and software engineering, focusing on production-ready ML systems, scalability, and performance. The ideal candidate has strong experience in Python, ML frameworks, data pipelines, and cloud platforms, and is comfortable working … unsupervised, and deep learning techniques as appropriate. Perform feature engineering, model tuning, and validation to improve accuracy and performance. 2. Productionisation & Deployment Deploy ML models into production using scalable, reliable architectures. Build and maintain APIs or batch pipelines for model inference. Monitor model performance, data drift, and retraining needs. ...

learning models that power data-driven products and business solutions. This role bridges data science and software engineering, focusing on production-ready ML systems, scalability, and performance. The ideal candidate has strong experience in Python, ML frameworks, data pipelines, and cloud platforms, and is comfortable working … unsupervised, and deep learning techniques as appropriate. Perform feature engineering, model tuning, and validation to improve accuracy and performance. 2. Productionisation & Deployment Deploy ML models into production using scalable, reliable architectures. Build and maintain APIs or batch pipelines for model inference. Monitor model performance, data drift, and retraining needs. ...

learning models that power data-driven products and business solutions. This role bridges data science and software engineering, focusing on production-ready ML systems, scalability, and performance. The ideal candidate has strong experience in Python, ML frameworks, data pipelines, and cloud platforms, and is comfortable working … unsupervised, and deep learning techniques as appropriate. Perform feature engineering, model tuning, and validation to improve accuracy and performance. 2. Productionisation & Deployment Deploy ML models into production using scalable, reliable architectures. Build and maintain APIs or batch pipelines for model inference. Monitor model performance, data drift, and retraining needs. ...

learning models that power data-driven products and business solutions. This role bridges data science and software engineering, focusing on production-ready ML systems, scalability, and performance. The ideal candidate has strong experience in Python, ML frameworks, data pipelines, and cloud platforms, and is comfortable working … unsupervised, and deep learning techniques as appropriate. Perform feature engineering, model tuning, and validation to improve accuracy and performance. 2. Productionisation & Deployment Deploy ML models into production using scalable, reliable architectures. Build and maintain APIs or batch pipelines for model inference. Monitor model performance, data drift, and retraining needs. ...

learning models that power data-driven products and business solutions. This role bridges data science and software engineering, focusing on production-ready ML systems, scalability, and performance. The ideal candidate has strong experience in Python, ML frameworks, data pipelines, and cloud platforms, and is comfortable working … unsupervised, and deep learning techniques as appropriate. Perform feature engineering, model tuning, and validation to improve accuracy and performance. 2. Productionisation & Deployment Deploy ML models into production using scalable, reliable architectures. Build and maintain APIs or batch pipelines for model inference. Monitor model performance, data drift, and retraining needs. ...

learning models that power data-driven products and business solutions. This role bridges data science and software engineering, focusing on production-ready ML systems, scalability, and performance. The ideal candidate has strong experience in Python, ML frameworks, data pipelines, and cloud platforms, and is comfortable working … unsupervised, and deep learning techniques as appropriate. Perform feature engineering, model tuning, and validation to improve accuracy and performance. 2. Productionisation & Deployment Deploy ML models into production using scalable, reliable architectures. Build and maintain APIs or batch pipelines for model inference. Monitor model performance, data drift, and retraining needs. ...

learning models that power data-driven products and business solutions. This role bridges data science and software engineering, focusing on production-ready ML systems, scalability, and performance. The ideal candidate has strong experience in Python, ML frameworks, data pipelines, and cloud platforms, and is comfortable working … unsupervised, and deep learning techniques as appropriate. Perform feature engineering, model tuning, and validation to improve accuracy and performance. 2. Productionisation & Deployment Deploy ML models into production using scalable, reliable architectures. Build and maintain APIs or batch pipelines for model inference. Monitor model performance, data drift, and retraining needs. ...

learning models that power data-driven products and business solutions. This role bridges data science and software engineering, focusing on production-ready ML systems, scalability, and performance. The ideal candidate has strong experience in Python, ML frameworks, data pipelines, and cloud platforms, and is comfortable working … unsupervised, and deep learning techniques as appropriate. Perform feature engineering, model tuning, and validation to improve accuracy and performance. 2. Productionisation & Deployment Deploy ML models into production using scalable, reliable architectures. Build and maintain APIs or batch pipelines for model inference. Monitor model performance, data drift, and retraining needs. ...

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 ...

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 ...

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 ...

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 ...

with prompt engineering, RAG architectures, and multimodal models. Contribute to internal tools for monitoring, testing, and improving AI performance. Stay on the edge of ML/AI research — we give you time and resources to explore, learn, and publish. What We’re Looking For 0–3 years of experience … environment. Is curious, ambitious, and eager to build real AI systems that have an impact. What You’ll Get Hands-on mentorship from senior ML engineers, AI researchers, and founders. Freedom to experiment with state-of-the-art models, tools, and frameworks. Modern tech stack (Python, LangChain, Hugging Face, OpenAI ...

seeking an ambitious and intellectually curious Junior Data Scientist to join a fast-growing, forward-thinking team working at the forefront of data science, machine learning, and applied AI. This is an excellent opportunity for a recent Master's graduate eager to apply their academic expertise to solving … real-world challenges—whether it's predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You'll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What ...

accelerate materials innovation and transform manufacturing. Role Overview We are seeking a Machine Learning Engineer to design, develop, and validate novel ML models that optimise manufacturing processes and material composition. You will collaborate closely with process engineers and materials scientists, identifying meaningful features and translating complex datasets into … impactful insights. You will also help advance our internal ML platforms to support model adoption and scale. In this role, you will: Build robust ML and MLOps pipelines for scalable, reproducible model development, deployment, and monitoring. Use tools such as Airflow for workflow orchestration and MLflow for experiment tracking, model ...

Machine Learning Engineer Hybrid Working - UK Wide - 2 Days a Week On Site Financial Services Lorien's leading banking client is looking for a Machine Learning Engineer to join the growing data science and AI team. You'll play a key role in building and operating robust ML pipelines and serving systems for classic ML and deep learning models, including those that underpin GenAI features. This role is based UK Wide. This ...

LLMs) and machine learning security. Following a successful Series A funding round, they're expanding their team and looking for a talented ML Scientist to help shape the future of intelligent, secure systems. You'll be part of a strong research group located near King's Cross, working … hybrid environment alongside accomplished ML scientists with publications at top-tier conferences. Experience Required MSc or PhD in Computer Science, Machine Learning, or a related discipline Strong hands-on experience with transformer-based models/LLMs Proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) Proven ...

Platform solutions with Microsoft 365 services (like Teams and SharePoint) and other third-party systems or APIs. Data & AI Integration: Utilize AI Builder and machine learning models to add intelligence to applications and automations. Collaboration: Work closely with business analysts, stakeholders, and end-users to understand requirements … ensure solutions meet business objectives. Essential Skills & Knowledge: Microsoft Power Platform: Deep knowledge of Power Apps, Power Automate, Power BI, and Dataverse. AI & Machine Learning: Experience with AI automation tools, machine learning models, and AI Builder for enhanced functionality. Copilot Studio: Expertise in building and deploying ...

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 ...

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 ...

Purpose of position As a Senior Data Engineer, you will play a pivotal role in our AI/ML workstream, you’ll work closely with business teams and data scientists to design, maintain, and improve machine learning applications. Your main responsibilities will include managing existing ML workloads … building new batch and on-demand pipelines to support advanced AI/ML models. You’ll also contribute to developing Generative AI solutions and applications for the emerging Agentic Era. You’ll collaborate with a global team to create scalable data architectures optimised for AI/ML, source and prepare ...