1 to 25 of 29 Remote Feature Engineering Jobs in London

multiple internal and external sources. Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies. Design and implement data pipelines for model-ready datasets in collaboration with data engineering teams. Apply feature engineering and selection techniques to improve model accuracy and interpretability. Develop and validate machine learning and statistical models for prediction, classification, clustering, or optimization. … on project requirements. Evaluate models using appropriate metrics and perform hyperparameter tuning for optimal performance. Convert proof-of-concept models into production-grade pipelines in collaboration with MLOps and engineering teams. Required: Translate model outcomes into actionable insights through clear storytelling and visualizations. Build dashboards and reports using Power BI, Tableau, or Python-based visualization tools. Communicate findings to More ❯

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 has grown significantly over the last 18 months, with strong ongoing … ML pipelines for training, deployment, monitoring, and retraining at scale. Working with data scientists to take models from development to production-grade systems, ensuring scalability, reproducibility, and robustness. Automating feature engineering and data pipeline processes, ensuring reproducibility and auditability. Implementing monitoring and observability to detect drift, bias, and performance degradation, and setting up rollback/recovery processes. Using … Pipelines, Kubeflow, Weights & Biases) for experiment tracking, model registry, and automated deployment. Leveraging Docker/Kubernetes and workflow orchestration tools (Airflow, Prefect, Dagster). Collaborating with product, design, and engineering teams to deliver ML features that directly impact customer experience. Translating model performance into business metrics (e.g., accuracy vs cost/latency trade-offs). Monitoring deployed solutions in More ❯

machine learning and AI models Designing, developing, and deploying LLM applications (e.g. GPT, LLaMA, Claude) integrated with RAG pipelines Implementing end-to-end workflows: from data acquisition, cleaning, and feature engineering to model training, deployment, and monitoring Building scalable pipelines and APIs for AI services in cloud environments (AWS, Azure, or GCP) Collaborating with engineers, product teams, and … advancements in AI and machine learning What We’re Looking For: A recently completed Master’s degree from a Russell Group university in Artificial Intelligence, Computer Science, Data Science, Engineering, Mathematics, or a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow … remote work 📈 Career Growth: Mentorship, structured training, and clear progression paths 🛠 Modern Tech Stack: Hands-on with the latest AI and cloud tools 🤝 Collaborative Culture: Join a supportive, innovative engineering team ✨ Additional Perks: Pension scheme, private healthcare, and wellbeing initiatives How to Apply: If you’re excited by the opportunity to apply your academic and project work to real More ❯

machine learning and AI models Designing, developing, and deploying LLM applications (e.g. GPT, LLaMA, Claude) integrated with RAG pipelines Implementing end-to-end workflows: from data acquisition, cleaning, and feature engineering to model training, deployment, and monitoring Building scalable pipelines and APIs for AI services in cloud environments (AWS, Azure, or GCP) Collaborating with engineers, product teams, and … advancements in AI and machine learning What We’re Looking For: A recently completed Master’s degree from a Russell Group university in Artificial Intelligence, Computer Science, Data Science, Engineering, Mathematics, or a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow … remote work 📈 Career Growth: Mentorship, structured training, and clear progression paths 🛠 Modern Tech Stack: Hands-on with the latest AI and cloud tools 🤝 Collaborative Culture: Join a supportive, innovative engineering team ✨ Additional Perks: Pension scheme, private healthcare, and wellbeing initiatives How to Apply: If you’re excited by the opportunity to apply your academic and project work to real More ❯

machine learning and AI models Designing, developing, and deploying LLM applications (e.g. GPT, LLaMA, Claude) integrated with RAG pipelines Implementing end-to-end workflows: from data acquisition, cleaning, and feature engineering to model training, deployment, and monitoring Building scalable pipelines and APIs for AI services in cloud environments (AWS, Azure, or GCP) Collaborating with engineers, product teams, and … advancements in AI and machine learning What We’re Looking For: A recently completed Master’s degree from a Russell Group university in Artificial Intelligence, Computer Science, Data Science, Engineering, Mathematics, or a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow … remote work 📈 Career Growth: Mentorship, structured training, and clear progression paths 🛠 Modern Tech Stack: Hands-on with the latest AI and cloud tools 🤝 Collaborative Culture: Join a supportive, innovative engineering team ✨ Additional Perks: Pension scheme, private healthcare, and wellbeing initiatives How to Apply: If you’re excited by the opportunity to apply your academic and project work to real More ❯

machine learning and AI models Designing, developing, and deploying LLM applications (e.g. GPT, LLaMA, Claude) integrated with RAG pipelines Implementing end-to-end workflows: from data acquisition, cleaning, and feature engineering to model training, deployment, and monitoring Building scalable pipelines and APIs for AI services in cloud environments (AWS, Azure, or GCP) Collaborating with engineers, product teams, and … advancements in AI and machine learning What We’re Looking For: A recently completed Master’s degree from a Russell Group university in Artificial Intelligence, Computer Science, Data Science, Engineering, Mathematics, or a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow … remote work 📈 Career Growth: Mentorship, structured training, and clear progression paths 🛠 Modern Tech Stack: Hands-on with the latest AI and cloud tools 🤝 Collaborative Culture: Join a supportive, innovative engineering team ✨ Additional Perks: Pension scheme, private healthcare, and wellbeing initiatives How to Apply: If you’re excited by the opportunity to apply your academic and project work to real More ❯

in Python and familiar with key libraries such as TensorFlow, PyTorch, and scikit-learn.* Experience working with cloud platforms such as Azure, AWS, or GCP, ideally within a data engineering or MLOps context.* Strong understanding of data processing, feature engineering, and model evaluation techniques, with experience handling complex scientific datasets.* Excellent problem-solving and analytical skills, with More ❯

the following areas is a plus: finance, open banking, iGaming, startups, or enterprise companies dealing with real-time processing. Responsibilities You will use Python, with a strong grounding in feature engineering, model evaluation, and inference pipelines to help shape the future of our product offerings Lead data labeling at scale to produce ground-truth datasets and use ML … deployment and data workflows. Strong knowledge of statistical modelling, anomaly detection, clustering, and supervised/unsupervised learning Experience working with large-scale data Proven success collaborating with product and engineering teams to ship ML-based features and tools Strong communication skills and business acumen to present complex technical ideas to non-technical stakeholders Curious, proactive, and comfortable working in More ❯

the following areas is a plus: finance, open banking, iGaming, startups, or enterprise companies dealing with real-time processing. Responsibilities You will use Python, with a strong grounding in feature engineering, model evaluation, and inference pipelines to help shape the future of our product offerings Lead data labeling at scale to produce ground-truth datasets and use ML … deployment and data workflows. Strong knowledge of statistical modelling, anomaly detection, clustering, and supervised/unsupervised learning Experience working with large-scale data Proven success collaborating with product and engineering teams to ship ML-based features and tools Strong communication skills and business acumen to present complex technical ideas to non-technical stakeholders Curious, proactive, and comfortable working in More ❯

the following areas is a plus: finance, open banking, iGaming, startups, or enterprise companies dealing with real-time processing. Responsibilities You will use Python, with a strong grounding in feature engineering, model evaluation, and inference pipelines to help shape the future of our product offerings Lead data labeling at scale to produce ground-truth datasets and use ML … deployment and data workflows. Strong knowledge of statistical modelling, anomaly detection, clustering, and supervised/unsupervised learning Experience working with large-scale data Proven success collaborating with product and engineering teams to ship ML-based features and tools Strong communication skills and business acumen to present complex technical ideas to non-technical stakeholders Curious, proactive, and comfortable working in More ❯

the following areas is a plus: finance, open banking, iGaming, startups, or enterprise companies dealing with real-time processing. Responsibilities You will use Python, with a strong grounding in feature engineering, model evaluation, and inference pipelines to help shape the future of our product offerings Lead data labeling at scale to produce ground-truth datasets and use ML … deployment and data workflows. Strong knowledge of statistical modelling, anomaly detection, clustering, and supervised/unsupervised learning Experience working with large-scale data Proven success collaborating with product and engineering teams to ship ML-based features and tools Strong communication skills and business acumen to present complex technical ideas to non-technical stakeholders Curious, proactive, and comfortable working in More ❯

Key Skills Proficiency in Python and/or R for developing machine learning models. Experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn. Strong understanding of data preprocessing, feature engineering, and model evaluation techniques. Familiarity with cloud platforms like AWS, GCP, or Azure for deploying ML solutions. Knowledge of version control systems (e.g., Git) and CI/ More ❯

and product managers, to deliver robust AI solutions. Key Skills Proficiency in Python, TensorFlow, or PyTorch Experience with machine learning algorithms and frameworks Strong understanding of data pre-processing, feature engineering, and model evaluation Familiarity with cloud services (AWS, GCP, Azure) and their AI/ML offerings Knowledge of natural language processing (NLP) and computer vision is a More ❯

and product managers, to deliver robust AI solutions. Key Skills Proficiency in Python, TensorFlow, or PyTorch Experience with machine learning algorithms and frameworks Strong understanding of data pre-processing, feature engineering, and model evaluation Familiarity with cloud services (AWS, GCP, Azure) and their AI/ML offerings Knowledge of natural language processing (NLP) and computer vision is a More ❯

help develop advanced machine learning models that predict and prevent equipment failures in large-scale industrial operations. This is an exciting opportunity to apply data science to real-world engineering challenges , using rich, high-frequency data from complex machinery. Their AI-driven predictive maintenance platform is built on years of operational data and designed to help clients reduce downtime … maintenance strategies. Develop and maintain data pipelines using tools like Apache Airflow for efficient workflows. Use MLflow for experiment tracking, model versioning, and deployment management. Contribute to data cleaning, feature engineering, and model evaluation processes. Collaborate with engineers and data teams to better understand equipment behavior and enhance model performance. What We're Looking For A Bachelor's … degree in Computer Science, Mathematics, Electrical Engineering, or a related field. Strong experience with Python and data science libraries (Pandas, Scikit-learn, etc.). Solid understanding of machine learning concepts and algorithms . Interest in working with real-world industrial or sensor data . Exposure to Apache Airflow and/or MLflow (through coursework or experience) is a plus. More ❯

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 scientists, and the wider engineering team to ensure our models are accurate, explainable, and seamlessly integrated into our lending platform. What You’ll Do Lead the design, training, and optimisation of credit risk and … XGBoost and scikit-learn. Responsible for creating proprietary data enrichment algorithms. Guide the evolution toward a self-learning model framework, improving automation and adaptability over time. Design and oversee feature testing and evaluation to enhance predictive performance and interpretability. Use BigQuery and GCP tools (including CloudRun) to manage and process large-scale datasets efficiently. Ensure models are explainable and … 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 techniques and bring new ideas to improve scalability, performance, and transparency. What We’re Looking For 4+ years of hands-on experience More ❯

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 scientists, and the wider engineering team to ensure our models are accurate, explainable, and seamlessly integrated into our lending platform. What You’ll Do Lead the design, training, and optimisation of credit risk and … XGBoost and scikit-learn. Responsible for creating proprietary data enrichment algorithms. Guide the evolution toward a self-learning model framework, improving automation and adaptability over time. Design and oversee feature testing and evaluation to enhance predictive performance and interpretability. Use BigQuery and GCP tools (including CloudRun) to manage and process large-scale datasets efficiently. Ensure models are explainable and … 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 techniques and bring new ideas to improve scalability, performance, and transparency. What We’re Looking For 4+ years of hands-on experience More ❯

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 scientists, and the wider engineering team to ensure our models are accurate, explainable, and seamlessly integrated into our lending platform. What You’ll Do Lead the design, training, and optimisation of credit risk and … XGBoost and scikit-learn. Responsible for creating proprietary data enrichment algorithms. Guide the evolution toward a self-learning model framework, improving automation and adaptability over time. Design and oversee feature testing and evaluation to enhance predictive performance and interpretability. Use BigQuery and GCP tools (including CloudRun) to manage and process large-scale datasets efficiently. Ensure models are explainable and … 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 techniques and bring new ideas to improve scalability, performance, and transparency. What We’re Looking For 4+ years of hands-on experience More ❯

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 scientists, and the wider engineering team to ensure our models are accurate, explainable, and seamlessly integrated into our lending platform. What You’ll Do Lead the design, training, and optimisation of credit risk and … XGBoost and scikit-learn. Responsible for creating proprietary data enrichment algorithms. Guide the evolution toward a self-learning model framework, improving automation and adaptability over time. Design and oversee feature testing and evaluation to enhance predictive performance and interpretability. Use BigQuery and GCP tools (including CloudRun) to manage and process large-scale datasets efficiently. Ensure models are explainable and … 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 techniques and bring new ideas to improve scalability, performance, and transparency. What We’re Looking For 4+ years of hands-on experience More ❯

our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. 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 … break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the More ❯

our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. 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 … break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the More ❯

team and focus on people development and career growth. You will manage model tuning and development efforts, support regulatory deliverables, and collaborate with cross-functional teams including Compliance, Data Engineering, and Technology. What we'll offer you A healthy, engaged and well-supported workforce are better equipped to do their best work and, more importantly, enjoy their lives inside … leave per year Your key responsibilities Leading the design and calibration of models for NLS and TS systems, ensuring optimal detection quality and manageable alert volumes Performing data exploration, feature engineering, and statistical analysis to inform tuning strategies Documenting model logic and outcomes in line with governance and validation standards Take ownership of specific model projects, from requirements More ❯

in the following areas is a plus: finance, open banking, iGaming, startups, or enterprise companies dealing with real-time processing. You will use Python, with a strong grounding in feature engineering, model evaluation, and inference pipelines to help shape the future of our product offerings Lead data labeling at scale to produce ground-truth datasets and use ML … and deploying ML models in Python SQL skills and familiarity with AWS for deployment and data workflows. Experience working with large-scale data Proven success collaborating with product and engineering teams to ship ML-based features and tools Proficiency with data visualisation tools such as Tableau, PowerBI Demonstrated ability to design and validate features using transactional and behavioral data More ❯

is placing data science at the heart of its strategy, investing heavily in both classic ML and next-generation AI capabilities. This is a company that blends modern product engineering with a fast-moving, high-ownership culture. Their environment encourages experimentation, cross-functional collaboration, and the freedom to shape what “great” looks like in machine learning at scale. The … of their real-time modelling infrastructure. This is a hybrid hands-on/leadership role, ideal for someone who thrives at the intersection of applied research, platform integration, and engineering-minded data science. What You’ll Be Doing Build and deploy a wide variety of models spanning classification, regression, propensity scoring, and LLM-based use cases Spearhead the entire … s GenAI efforts. The team have multiple LLM projects running but would love a technical leader in this area Own the end-to-end lifecycle of ML projects, from feature engineering to deployment and monitoring Define best practices for model testing, automation, and continuous improvement within a high-performing team Act as a technical thought leader, partnering with More ❯

is placing data science at the heart of its strategy, investing heavily in both classic ML and next-generation AI capabilities. This is a company that blends modern product engineering with a fast-moving, high-ownership culture. Their environment encourages experimentation, cross-functional collaboration, and the freedom to shape what “great” looks like in machine learning at scale. The … of their real-time modelling infrastructure. This is a hybrid hands-on/leadership role, ideal for someone who thrives at the intersection of applied research, platform integration, and engineering-minded data science. What You’ll Be Doing Build and deploy a wide variety of models spanning classification, regression, propensity scoring, and LLM-based use cases Spearhead the entire … s GenAI efforts. The team have multiple LLM projects running but would love a technical leader in this area Own the end-to-end lifecycle of ML projects, from feature engineering to deployment and monitoring Define best practices for model testing, automation, and continuous improvement within a high-performing team Act as a technical thought leader, partnering with More ❯