1 to 25 of 443 Remote Machine Learning Jobs in the South East

who thrives in environments where reliability, scale, and impact truly matter. At Rightmove, you'll join a close-knit, collaborative AI team that's developing, shipping and operating live ML/AI services that help Rightmove deliver exceptional experiences and value to consumers, our partners and all our stakeholders across the UK property market. You'll be at the heart … deploying, and operating machine learning systems that leverage Rightmove's data at large scale. You'll have the opportunity to shape best practices, own and grow the ML Ops discipline, and help us move from first launches to robust, sustainable production. In this role, you will work in a cross-functional team to productionise machine learning … You'll collaborate closely with data scientists, engineers, and product teams to automate workflows, monitor performance, and retrain models as needed. You'll bring a passion for building reliable ML infrastructure, a strong technical foundation in modern machine learning engineering, and a track record of working in environments where reliability and scale are paramount. Our Data & Analytics team More ❯

who thrives in environments where reliability, scale, and impact truly matter. At Rightmove, you'll join a close-knit, collaborative AI team that's developing, shipping and operating live ML/AI services that help Rightmove deliver exceptional experiences and value to consumers, our partners and all our stakeholders across the UK property market. You'll be at the heart … deploying, and operating machine learning systems that leverage Rightmove's data at large scale. You'll have the opportunity to shape best practices, own and grow the ML Ops discipline, and help us move from first launches to robust, sustainable production. In this role, you will work in a cross-functional team to productionise machine learning … You'll collaborate closely with data scientists, engineers, and product teams to automate workflows, monitor performance, and retrain models as needed. You'll bring a passion for building reliable ML infrastructure, a strong technical foundation in modern machine learning engineering, and a track record of working in environments where reliability and scale are paramount. Our Data & Analytics team More ❯

learning solutions, aligned to operational goals and governance standards. Prepare and transform data for modelling using Python and Azure-native tools, ensuring quality and consistency across the ML and AI lifecycles. Evaluate, and deploy models using AutoML, MLflow, and custom pipelines, with a focus on performance, scalability, and maintainability. Monitor model performance, detect drift, and implement retraining strategies … to maintain relevance and accuracy. Apply responsible AI principles including fairness, explainability, and privacy to support ethical and transparent model development. Collaborate with cross-functional teams to integrate ML and AI solutions into business processes, improving engagement, productivity, and decision-making. Support our clients maintain and optimise Azure ML environments to deliver reproducible experimentation and efficient deployment. Person, Skills & Experience … Certified in DP-100 Azure Data Scientist Associate (mandatory). Confident working independently or collaboratively to support solution design, delivery, and governance across the ML and AI lifecycle. Experienced in designing, training, registering, and deploying models using Azure Machine Learning (AML), AutoML, and MLflow. Proficient in Python, pandas, and scikit-learn for data science and feature engineering, with More ❯

learning models and AI-driven solutions to address business challenges. Collaborate with data scientists to transition prototypes into production-ready systems . Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment. Optimise model performance, scalability, and reliability using MLOps best practices. Work with large-scale structured and unstructured datasets for model training and … validation. Implement model monitoring, versioning, and retraining processes to ensure continuous improvement. Collaborate cross-functionally with engineering, data, and product teams to integrate ML solutions into production environments. Stay current with emerging trends in AI/ML technologies and contribute to innovation within the organisation. Required Skills & Experience Proven experience (3–5+ years) as a Machine Learning Engineer … lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications Bachelor’s or Master’s degree in Computer Science , Data Science , Mathematics , or More ❯

learning models and AI-driven solutions to address business challenges. Collaborate with data scientists to transition prototypes into production-ready systems . Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment. Optimise model performance, scalability, and reliability using MLOps best practices. Work with large-scale structured and unstructured datasets for model training and … validation. Implement model monitoring, versioning, and retraining processes to ensure continuous improvement. Collaborate cross-functionally with engineering, data, and product teams to integrate ML solutions into production environments. Stay current with emerging trends in AI/ML technologies and contribute to innovation within the organisation. Required Skills & Experience Proven experience (3–5+ years) as a Machine Learning Engineer … lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications Bachelor’s or Master’s degree in Computer Science , Data Science , Mathematics , or More ❯

learning models and AI-driven solutions to address business challenges. Collaborate with data scientists to transition prototypes into production-ready systems . Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment. Optimise model performance, scalability, and reliability using MLOps best practices. Work with large-scale structured and unstructured datasets for model training and … validation. Implement model monitoring, versioning, and retraining processes to ensure continuous improvement. Collaborate cross-functionally with engineering, data, and product teams to integrate ML solutions into production environments. Stay current with emerging trends in AI/ML technologies and contribute to innovation within the organisation. Required Skills & Experience Proven experience (3–5+ years) as a Machine Learning Engineer … lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications Bachelor’s or Master’s degree in Computer Science , Data Science , Mathematics , or More ❯

the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Lead Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data … Pipeline Engineering: Construct and maintain 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 experiments to evaluate model efficacy … ll bring Demonstrated expertise in the full lifecycle of machine learning, from model development and deployment to monitoring and maintenance. Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative More ❯

the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Lead Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data … Pipeline Engineering: Construct and maintain 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 experiments to evaluate model efficacy … ll bring Demonstrated expertise in the full lifecycle of machine learning, from model development and deployment to monitoring and maintenance. Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative More ❯

the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Lead Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data … Pipeline Engineering: Construct and maintain 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 experiments to evaluate model efficacy … ll bring Demonstrated expertise in the full lifecycle of machine learning, from model development and deployment to monitoring and maintenance. Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative More ❯

that power model training and deployment. Why this role? Build data systems that enable cutting-edge machine learning at scale Work in a high-calibre team alongside ML researchers and engineers Competitive compensation that matches or exceeds top industry benchmarks Your responsibilities Designing and implementing scalable, high-performance data pipelines to support model training and experimentation Collaborating with … machine learning researchers and software engineers to ensure robust integration of data into ML workflows Writing clean, production-level code to support large-scale model development and deployment Optimising storage, retrieval, and processing for complex datasets, including text-heavy/NLP data Evaluating and adopting new technologies to enhance machine learning infrastructure What you bring Strong … software engineering experience, with a focus on writing high-quality, scalable code Experience in data engineering or data-intensive systems, ideally within ML-driven teams Familiarity with machine learning workflows - especially model training and experimentation Proficiency in programming languages such as Python, Scala, or Java Cloud experience (AWS, GCP, or Azure), plus modern data technologies (e.g. Spark, Kafka More ❯

that power model training and deployment. Why this role? Build data systems that enable cutting-edge machine learning at scale Work in a high-calibre team alongside ML researchers and engineers Competitive compensation that matches or exceeds top industry benchmarks Your responsibilities Designing and implementing scalable, high-performance data pipelines to support model training and experimentation Collaborating with … machine learning researchers and software engineers to ensure robust integration of data into ML workflows Writing clean, production-level code to support large-scale model development and deployment Optimising storage, retrieval, and processing for complex datasets, including text-heavy/NLP data Evaluating and adopting new technologies to enhance machine learning infrastructure What you bring Strong … software engineering experience, with a focus on writing high-quality, scalable code Experience in data engineering or data-intensive systems, ideally within ML-driven teams Familiarity with machine learning workflows - especially model training and experimentation Proficiency in programming languages such as Python, Scala, or Java Cloud experience (AWS, GCP, or Azure), plus modern data technologies (e.g. Spark, Kafka More ❯

Machine Learning Engineer Machine Learning Engineer – AI for Advanced Materials – Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We’re looking for a Machine Learning Engineer to join a rapidly scaling deep-tech … printing , our client is transforming the way metal components are conceived, tested, and produced — enabling breakthroughs in aerospace, energy, and beyond. This is a rare chance to apply your ML expertise to problems that have a tangible, physical impact — from inventing new alloys to optimising complex manufacturing processes. You’ll collaborate with leading data scientists, engineers, and materials researchers to … build models that drive real-world innovation. Expect to design, validate, and deploy state-of-the-art ML pipelines that move seamlessly from concept to production. If you thrive in fast-paced, intellectually charged environments where every model could change an industry, you’ll fit right in. Our client is seeking Machine Learning Engineers with experience in some More ❯

Machine Learning Engineer Machine Learning Engineer – AI for Advanced Materials – Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We’re looking for a Machine Learning Engineer to join a rapidly scaling deep-tech … printing , our client is transforming the way metal components are conceived, tested, and produced — enabling breakthroughs in aerospace, energy, and beyond. This is a rare chance to apply your ML expertise to problems that have a tangible, physical impact — from inventing new alloys to optimising complex manufacturing processes. You’ll collaborate with leading data scientists, engineers, and materials researchers to … build models that drive real-world innovation. Expect to design, validate, and deploy state-of-the-art ML pipelines that move seamlessly from concept to production. If you thrive in fast-paced, intellectually charged environments where every model could change an industry, you’ll fit right in. Our client is seeking Machine Learning Engineers with experience in some More ❯

Machine Learning Engineer Machine Learning Engineer - AI for Advanced Materials - Oxford/Remote (UK) (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly … printing , our client is transforming the way metal components are conceived, tested, and produced - enabling breakthroughs in aerospace, energy, and beyond. This is a rare chance to apply your ML expertise to problems that have a tangible, physical impact - from inventing new alloys to optimising complex manufacturing processes. You'll collaborate with leading data scientists, engineers, and materials researchers to … build models that drive real-world innovation. Expect to design, validate, and deploy state-of-the-art ML pipelines that move seamlessly from concept to production. If you thrive in fast-paced, intellectually charged environments where every model could change an industry, you'll fit right in. Our client is seeking Machine Learning Engineers with experience in some More ❯

Machine Learning/Data Engineer £700-750/day overall assignment rate to umbrella Fully remote 3-6 month initial Apply today to join a forward-thinking, tech-driven FTSE 100 organisation using data science and AI to enhance customer experience, optimise supply chains and drive sustainable growth. With 40% of sales from sustainable products … this is a company that combines scale, innovation and purpose. As a Machine Learning Engineer, you'll help maintain the stability and performance of core data and ML systems across Europe. This technical engineering role focuses on reliability, optimisation and critical fixes, ideal if you excel at investigating and debugging complex data flows and ML issues in live … Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services). Expertise: Solid understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random More ❯

into scalable production systems. Experiment 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 in Machine Learning, Data … in a fast-moving startup 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 API, Pinecone, Kubernetes, etc.). … and shape the product roadmap. An environment that values learning, creativity, and personal growth over bureaucracy. Perfect For Graduates or junior engineers with a passion for AI/ML looking to break into applied LLM engineering. Researchers or data scientists eager to move from theory to real-world deployment. Builders who want to join an early-stage company where More ❯

for our recommender systems and search algorithms,building the core infrastructure that powers millions of meaningful connections. Working in theSearch & Match domain, you willbe focusing on deploying and scaling machine learning models, particularly large language models (LLMs). You will collaborate with data scientists to make sure our models are efficient and can be properly optimized for cost … love to hear from you! You will play a vital role as we reimagine the labour market to make it work for everybody. Your responsibilities: Collaborate with data scientists, ML Engineers, and backend engineers within an Agile environment Deploy and scale ML models, particularly large language models (LLMs) Build and maintain scalable pipelines and services to support real-time ML … improve recommender systems Build and work with modern API and microservices architectures Qualifications Strong foundation in Python Experience with machine learning, familiar with Huggingface, Pytorch, and similar ML tools and packages Familiarity with deploying and scaling ML models in the cloud, particularly with AWS and SageMaker Understanding of DevOps processes and tools: CI/CD, Docker, Terraform, and More ❯

We are partnering with an early-stage, mission-driven company at the intersection of AI and national defence to appoint exceptional Machine Learning Engineers . This fast-growing organisation is transforming mission-critical combat planning and operational decision-making by building next-generation AI software tools for Western forces. Founded in 2023, the company has already secured significant … leaders. They combine deep sector knowledge with cutting-edge design and software engineering expertise to deliver state-of-the-art SaaS capabilities leveraging NLP, GenAI, Computer Vision, and Reinforcement Learning technologies. Position location (hybrid) : London (Shoreditch) or Paris (Le Marais) We are seeking Machine Learning Engineers who are passionate about using AI technology to solve complex, real … the product team, to identify and capitalise on high-impact opportunities Keep the company at the forefront of innovation by exploring and applying the latest research Requirements: MSc in Machine Learning, Computer Science, or a related field 5+ years of experience in machine learning, with an expertise in modelling, prototyping, and evaluation Strong software engineering skills More ❯

We are partnering with an early-stage, mission-driven company at the intersection of AI and national defence to appoint exceptional Machine Learning Engineers . This fast-growing organisation is transforming mission-critical combat planning and operational decision-making by building next-generation AI software tools for Western forces. Founded in 2023, the company has already secured significant … leaders. They combine deep sector knowledge with cutting-edge design and software engineering expertise to deliver state-of-the-art SaaS capabilities leveraging NLP, GenAI, Computer Vision, and Reinforcement Learning technologies. Position location (hybrid) : London (Shoreditch) or Paris (Le Marais) We are seeking Machine Learning Engineers who are passionate about using AI technology to solve complex, real … the product team, to identify and capitalise on high-impact opportunities Keep the company at the forefront of innovation by exploring and applying the latest research Requirements: MSc in Machine Learning, Computer Science, or a related field 5+ years of experience in machine learning, with an expertise in modelling, prototyping, and evaluation Strong software engineering skills More ❯

We are partnering with an early-stage, mission-driven company at the intersection of AI and national defence to appoint exceptional Machine Learning Engineers . This fast-growing organisation is transforming mission-critical combat planning and operational decision-making by building next-generation AI software tools for Western forces. Founded in 2023, the company has already secured significant … leaders. They combine deep sector knowledge with cutting-edge design and software engineering expertise to deliver state-of-the-art SaaS capabilities leveraging NLP, GenAI, Computer Vision, and Reinforcement Learning technologies. Position location (hybrid) : London (Shoreditch) or Paris (Le Marais) We are seeking Machine Learning Engineers who are passionate about using AI technology to solve complex, real … the product team, to identify and capitalise on high-impact opportunities Keep the company at the forefront of innovation by exploring and applying the latest research Requirements: MSc in Machine Learning, Computer Science, or a related field 5+ years of experience in machine learning, with an expertise in modelling, prototyping, and evaluation Strong software engineering skills More ❯

team. The PlayStation brand falls under Sony Interactive Entertainment, a wholly-owned subsidiary of Sony Group Corporation. Role Overview: We are looking for an independent, dedicated Senior or Staff Machine Learning Engineer to join the Visual Computing Group (VCG) and contribute to … redefining the world of game play and live streaming via advanced R&D. VCG's mission is to design and deploy advanced neural networks and machine learning (ML) for game rendering and streaming systems of SIE that exceed the state-of-the-art in runtime efficiency, visual quality and latency. What you'll be doing: Develop and improve … the team in core R&D work with other teams within Sony Interactive Entertainment What we're looking for: PhD or MSc in Computer Science, Electronic Engineering, Artificial Intelligence, Machine Learning, Computer Graphics or a related field, or equivalent skills evidenced by work experience in the specific domain of the post Strong background in: TensorFlow or PyTorch; Python More ❯

manage risk. The Role As a Senior Machine Learning Engineer, you’ll take technical ownership of our credit risk model suite — iterating, optimising, and deploying production-ready ML systems that drive real-world impact. You’ll remain hands-on in design and experimentation while mentoring 1–2 junior ML engineers. You’ll collaborate closely with credit analysts, data … GCP tools (including CloudRun) to manage and process large-scale datasets efficiently. Ensure models are explainable and compliant, collaborating with credit and risk teams to interpret outcomes. Mentor junior ML engineers through code reviews, technical guidance, and project planning. Work with software engineers to productionise models (deployment and pipelines handled by the engineering team). Stay ahead of emerging ML … experience in applied machine learning (preferably in financial services or another regulated domain). Proven ability to design, train, and evaluate models using Python, XGBoost, and related ML frameworks. Strong experience with SQL and BigQuery; familiarity with GCP infrastructure. Comfortable working end-to-end from data exploration through validation and interpretation. Understanding of explainable AI and model governance More ❯

manage risk. The Role As a Senior Machine Learning Engineer, you’ll take technical ownership of our credit risk model suite — iterating, optimising, and deploying production-ready ML systems that drive real-world impact. You’ll remain hands-on in design and experimentation while mentoring 1–2 junior ML engineers. You’ll collaborate closely with credit analysts, data … GCP tools (including CloudRun) to manage and process large-scale datasets efficiently. Ensure models are explainable and compliant, collaborating with credit and risk teams to interpret outcomes. Mentor junior ML engineers through code reviews, technical guidance, and project planning. Work with software engineers to productionise models (deployment and pipelines handled by the engineering team). Stay ahead of emerging ML … experience in applied machine learning (preferably in financial services or another regulated domain). Proven ability to design, train, and evaluate models using Python, XGBoost, and related ML frameworks. Strong experience with SQL and BigQuery; familiarity with GCP infrastructure. Comfortable working end-to-end from data exploration through validation and interpretation. Understanding of explainable AI and model governance More ❯

manage risk. The Role As a Senior Machine Learning Engineer, you’ll take technical ownership of our credit risk model suite — iterating, optimising, and deploying production-ready ML systems that drive real-world impact. You’ll remain hands-on in design and experimentation while mentoring 1–2 junior ML engineers. You’ll collaborate closely with credit analysts, data … GCP tools (including CloudRun) to manage and process large-scale datasets efficiently. Ensure models are explainable and compliant, collaborating with credit and risk teams to interpret outcomes. Mentor junior ML engineers through code reviews, technical guidance, and project planning. Work with software engineers to productionise models (deployment and pipelines handled by the engineering team). Stay ahead of emerging ML … experience in applied machine learning (preferably in financial services or another regulated domain). Proven ability to design, train, and evaluate models using Python, XGBoost, and related ML frameworks. Strong experience with SQL and BigQuery; familiarity with GCP infrastructure. Comfortable working end-to-end from data exploration through validation and interpretation. Understanding of explainable AI and model governance More ❯

impact of next-gen technologies — all while gaining hands-on experience that sets you apart in the job market. Responsibilities Support the design, testing, and evaluation of AI/ML models for fraud detection Analyse complex datasets to identify patterns, anomalies, and insights Collaborate with developers and data scientists to validate results and refine algorithms Assist in developing blockchain use … practical application in finance. Requirements Undergraduate degree in a technical field (e.g., Computer Science, Data Science, Mathematics, Engineering, Physics, or related) A strong and demonstrable interest in AI/ML and blockchain technologies - especially in their application to real-world business challenges Solid understanding of data analysis techniques and some familiarity with tools such as Python, SQL or Excel Excellent … Experience with Python libraries like Pandas, NumPy, or Scikit-learn Exposure to machine learning concepts or blockchain architecture Coursework or personal projects involving data analysis, AI/ML, or distributed systems Knowledge of data visualisation tools like Power BI or Tableau Benefits Fully funded, accredited qualifications Bespoke technical and business skills training A health cash plan 26 days More ❯