17 of 17 Remote/Hybrid Feature Engineering Jobs in London

techniques such as sequence prediction, intent modelling and imitation learning into production ready systems.You'll build end-to-end AI pipelines spanning data ingestion, feature engineering, model training, inference and monitoring, while applying causal inference to understand the real world impact of AI driven decisions.Collaborating with software engineers … causal inference and techniques for evaluating the impact of AI driven decisionsYou have experience building end-to-end ML pipelines, including data processing, feature engineering, training, inference and monitoringYou have strong engineering skills, with experience integrating AI services into production platforms using APIs, microservices or event driven ...

such as sequence prediction, intent modelling and imitation learning into production ready systems. You'll build end-to-end AI pipelines spanning data ingestion, feature engineering, model training, inference and monitoring, while applying causal inference to understand the real world impact of AI driven decisions. Collaborating with software … causal inference and techniques for evaluating the impact of AI driven decisions You have experience building end-to-end ML pipelines, including data processing, feature engineering, training, inference and monitoring You have strong engineering skills, with experience integrating AI services into production platforms using APIs, microservices ...

integrate LLM-powered solutions for tracing, evaluation, and production monitoring Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Design feature engineering approaches and contribute to feature store development Support production models through monitoring, performance analysis, and continuous improvement Apply responsible AI practices … quality controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures Familiarity with LLMOps tooling such as LangSmith, LangChain, or LangGraph Understanding of model evaluation, validation techniques, and production monitoring Experience working ...

integrate LLM-powered solutions for tracing, evaluation, and production monitoring Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Design feature engineering approaches and contribute to feature store development Support production models through monitoring, performance analysis, and continuous improvement Apply responsible AI practices … quality controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures Familiarity with LLMOps tooling such as LangSmith, LangChain, or LangGraph Understanding of model evaluation, validation techniques, and production monitoring Experience working ...

integrate LLM-powered solutions for tracing, evaluation, and production monitoring Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Design feature engineering approaches and contribute to feature store development Support production models through monitoring, performance analysis, and continuous improvement Apply responsible AI practices … quality controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures Familiarity with LLMOps tooling such as LangSmith, LangChain, or LangGraph Understanding of model evaluation, validation techniques, and production monitoring Experience working ...

EngineeringorEquivalent experience that shows you can deliver resultsTechnical skillsCore skillsStrong Python and SQL, with clean, maintainable codeSolid understanding of ML fundamentals. For example feature engineering, model selection, handling imbalanced data, choosing and interpreting metricsExperience with PyTorch or TensorFlowGenAI specificHands on experience with LLM APIs or open source models … provider. AWS, GCP or AzureFamiliar with Docker and CI/CD pipelinesExperience with managed ML platforms such as SageMaker, Vertex AI or Azure MLData engineering and MLOpsExperience with data warehouses such as Snowflake, BigQuery or RedshiftWorkflow orchestration using tools like Airflow or DagsterExperience with MLOps tools such as MLflow ...

analytics team & Tech partners in research to define the knowledge system, the agentic layer across the enterprise. You bring deep, hands-on AI/engineering expertise and the judgement to turn ambiguous technical problems into shipped, production-grade systems, while mentoring the engineers around you. Key Responsibilities This role … first production versions directly for use cases where the path is clear - before the Sr. Solutions Engineer takes them forward to scale. AI-Native Engineering Operate AI agent workflows (planning, coding, testing, review, documentation) for autonomous prototype delivery - selecting the right level of automation for each engagement. ...

will work hand in hand with the automation business and tech teams across R&D and manufacturing. You bring deep, hands-on AI/engineering expertise in Physical AI and the judgement to turn ambiguous technical problems into shipped, production-grade systems, while mentoring the engineers around you. … seeking professionals with the following required skills and qualifications to help us achieve our goals: Strong experience of full-stack or AI/ML engineering experience, including production deployments. Strong proficiency in Python and at least one of TypeScript/JavaScript, Go, or similar. Hands-on experience with GenAI ...

making embedded inside the teams instead of wasting time in wider forums, to reduce time to impact. You bring deep, hands-on AI/engineering expertise and the judgement to turn ambiguous technical problems into shipped, production-grade systems, while mentoring the engineers around you. Key Responsibilities This role … first production versions directly for use cases where the path is clear - before the Sr. Solutions Engineer takes them forward to scale. AI-Native Engineering Operate AI agent workflows (planning, coding, testing, review, documentation) for autonomous prototype delivery - selecting the right level of automation for each engagement. ...

that enable machine learning at scale.The Lead MLOps Engineer will design, build, and maintain the infrastructure that supports the full machine learning lifecycle, from feature generation and experimentation through to deployment, monitoring, and continuous improvement. You will play a key role in ensuring our predictive models and data products … platform architecture, helping shape the tooling, standards, and operating model used to deliver machine learning across the organisation.Develop and maintain automated workflows for feature engineering, model training, testing, deployment, monitoring, and retraining.Partner with Data Scientists and Data Engineers, and ML Engineers to operationalise predictive models and data products.Establish ...

develop, deploy, and optimise machine learning models that drive business outcomes. Key Responsibilities Design, build, and deploy machine learning models. Develop scalable data and feature engineering pipelines. Optimise model performance and production readiness. Work with large datasets to solve complex business challenges. Collaborate with Data Scientists, Engineers … skills. Experience building and deploying ML models in production. Hands-on knowledge of machine learning frameworks (Scikit-learn, TensorFlow, PyTorch). Data engineering and pipeline development experience. Cloud experience (AWS, Azure, or GCP). Strong understanding of software engineering best practices. Experience working in agile environments. Contract ...

business objectives Building prototypes and proof-of-concepts using Databricks and modern data platforms Translating business requirements into technical product specifications Designing data structures, feature sets, scoring methodologies, and model outputs Evaluating emerging AI technologies and analytical techniques for commercial application Supporting the launch and performance optimisation of data … predictive models, machine learning solutions, or advanced analytics products Ability to work with large-scale transactional, behavioural, or marketing datasets Understanding of data modelling, feature engineering, and analytical best practices Experience using Databricks or similar modern analytics platforms Knowledge of cloud-based data environments, ideally within Azure ecosystems ...

lending lifecycle. Key responsibilities include: Leading end-to-end validation of credit risk, machine learning and decisioning models Assessing model methodology, assumptions, data quality, feature engineering and target definitions Evaluating model performance, calibration, stability and robustness across different portfolios and customer segments Designing and maintaining model calibration ...

action.·Develop and validate propensity, churn, customer-value models and customer-level forecasts.·Work with large customer datasets spanning multiple years, owning data preparation, feature engineering and model evaluation.·Partner with marketing and CRM teams to activate model outputs in campaigns and measure their impact.·Take models through … production with engineering colleagues, monitoring performance and improving them over time.·Explain your recommendations to product teams, clients and senior stakeholders. What you'll bringYou'll be actively building models in Python and SQL, with examples you can explain from the original business question through to implementation and results. ...

closely with data acquisition and commercial teams to assess potential data investments. Applying techniques such as time series analysis, correlation analysis, hypothesis testing, and feature engineering. Identifying new opportunities to create valuable data products and customer insights. Managing and developing members of the Data Research team while raising technical … Proven experience evaluating, validating, and extracting value from new and unstructured datasets. Strong Python skills and a solid statistical background. Experience with data discovery, feature engineering, and transforming messy datasets into scalable analytical assets. Demonstrable experience leading open-ended research projects from concept through to business recommendation. Experience ...

with Data Scientists and wider technology teams to productionise models. Develop high quality Python code and support CI/CD processes. Create and optimise feature engineering and data preparation workflows. Monitor model performance and ensure ongoing reliability. Produce clear technical documentation and knowledge sharing materials. Engage with technical … learning solutions into production environments. Understanding of data processing, transformation and pipeline development. Experience building and maintaining end to end ML workflows. Solid software engineering and coding best practices. Exposure to modern AI and deep learning approaches including NLP and large language model related technologies. Reasonable Adjustments: Respect ...

with Data Scientists and wider technology teams to productionise models. Develop high quality Python code and support CI/CD processes. Create and optimise feature engineering and data preparation workflows. Monitor model performance and ensure ongoing reliability. Produce clear technical documentation and knowledge sharing materials. Engage with technical … learning solutions into production environments. Understanding of data processing, transformation and pipeline development. Experience building and maintaining end to end ML workflows. Solid software engineering and coding best practices. Exposure to modern AI and deep learning approaches including NLP and large language model related technologies. Reasonable Adjustments: Respect ...