1 to 25 of 28 Permanent Feature Engineering Jobs in the UK excluding London

systems: devices that operate autonomously, make decisions in real time, and remain reliable under the constraints that define actual field deployment. The Challenge The engineering challenge is significant. You will be responsible for the complete lifecycle of machine learning models that run on embedded devices. This means: From Sensor … transform this stream into a robust, real-time classification model that runs on hardware with severe constraints on memory, computation, and power. Engineering Under Constraint. Every machine learning decision you make has downstream consequences for embedded systems. A model that requires 512MB of RAM will ...

/Delta Lake) to the SageMaker-based "golden template" architecture, working to the pattern set by the Lead ML Ops Engineer Build and amend feature engineering pipelines, feature store integrations, and data access layers (S3, Glue, Lake Formation) supporting migrated models Implement parity and statistical testing … Work within CI/CD and IaC patterns for pipeline deployment; document runbooks and hand over to Evoke teams Collaborate daily with Evoke ML engineering, the CF team, and AWS ProServe counterparts Skills & experience Must-have Python/PySpark - Expert. Production data pipeline development, not analysis-only AWS data ...

/Delta Lake) to the SageMaker-based "golden template" architecture, working to the pattern set by the Lead ML Ops Engineer Build and amend feature engineering pipelines, feature store integrations, and data access layers (S3, Glue, Lake Formation) supporting migrated models Implement parity and statistical testing … Work within CI/CD and IaC patterns for pipeline deployment; document runbooks and hand over to Evoke teams Collaborate daily with Evoke ML engineering, the CF team, and AWS ProServe counterparts Skills & experience Must-have Python/PySpark - Expert. Production data pipeline development, not analysis-only AWS data ...

/Delta Lake) to the SageMaker-based "golden template" architecture, working to the pattern set by the Lead ML Ops Engineer Build and amend feature engineering pipelines, feature store integrations, and data access layers (S3, Glue, Lake Formation) supporting migrated models Implement parity and statistical testing … Work within CI/CD and IaC patterns for pipeline deployment; document runbooks and hand over to Evoke teams Collaborate daily with Evoke ML engineering, the CF team, and AWS ProServe counterparts Skills & experience Must-have Python/PySpark - Expert. Production data pipeline development, not analysis-only AWS data ...

individual-contributor role with significant technical and product ownership. You'll work across recommendations, personalisation, customer modelling and predictive modelling, partnering closely with Product, Engineering, MLOps, Commercial and Marketing to understand where Data Science can create the most value and how we should measure success. Key Responsibilities Own machine … identify high-value opportunities, shape ambiguous problems and determine whether Data Science is the right intervention. Independently select, build and improve modelling approaches, using feature engineering, tuning and appropriate algorithmic choices to improve performance. Design robust offline evaluation strategies, selecting metrics that reflect problem-specific behaviour and trade ...

science tools. Work closely with the Senior Data Architect and Development Team to ensure seamless integration of analytics reporting and models. Data Wrangling, EDA & Feature Engineering: Ensure the quality of data used for model development through meticulous data checking and cleaning practices. Process and transform raw, unstructured data … with demonstrable data science experience. Experience in the fundamentals of data science, including but not limited to: Data visualisation Exploratory Data Analysis Data Wrangling Feature Engineering Model Selection/Training/Tuning Experience in utilising data to drive insights related to football-specific questions. Highly skilled in advanced ...

OVERVIEW:This role exists to provide technical leadership within the data engineering team, setting the standard for engineering excellence while remaining deeply hands-on. The Lead Data Engineer drives the design and delivery of scalable, resilient data platforms and pipelines that underpin Gymshark's ambition … Technical Leadership: Own and drive the technical design and architecture of data pipelines, data models, and platform components across the team. Set and enforce engineering standards: code quality, testing, observability, security, and documentation, ensuring the whole team operates to them Lead technical discovery, design sessions, and code reviews, providing ...

Technical Leadership: Own and drive the technical design and architecture of data pipelines, data models, and platform components across the team. Set and enforce engineering standards: code quality, testing, observability, security, and documentation, ensuring the whole team operates to them Lead technical discovery, design sessions, and code reviews, providing … surfacing risks and proposing pragmatic solutions. Evaluate emerging tools and technologies (within the GCP ecosystem and beyond) and make grounded recommendations to the Data Engineering Manager. Work with the Data Engineering manager to find solutions to complex or ambiguous data engineering problems, unblocking the team and stakeholders. ...

across health and safety, sustainability and ethical behaviour. As a Data Scientist, you'll join a growing, highly skilled team spanning data science, data engineering, AI engineering and DevOps. You'll play a key role in building and deploying machine learning and AI solutions that power business applications … Models, with the chance to integrate innovative AI capabilities including LLMs, MCPs, APIs and enterprise data into production platforms. You'll work closely with Engineering and Product teams in a collaborative Agile environment, turning complex data and technology into solutions that deliver tangible business value. The role will include ...

across health and safety, sustainability and ethical behaviour. As a Data Scientist, you'll join a growing, highly skilled team spanning data science, data engineering, AI engineering and DevOps. You'll play a key role in building and deploying machine learning and AI solutions that power business applications … Models, with the chance to integrate innovative AI capabilities including LLMs, MCPs, APIs and enterprise data into production platforms. You'll work closely with Engineering and Product teams in a collaborative Agile environment, turning complex data and technology into solutions that deliver tangible business value. The role will include ...

have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III at JPMorganChase within the Corporate Technology, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products … uses these insights to drive improvements to coding hygiene and system architecture Required qualifications, capabilities, and skills Formal training or certification in software engineering concepts, plus 5+ years of applied experience building production Python systems, including web/API services (Flask or FastAPI) and the ML/NLP ecosystem ...

across recommendations, personalisation, customer modelling and predictive modelling. This is a hands‐on applied Data Science role where you’ll work closely with Product, Engineering, MLOps, Commercial and Marketing. You’ll turn clearly defined problems into practical ML solutions, evaluate whether they’re working and help bring them successfully …/B tests and other experiments, connecting model performance with customer behaviour and business outcomes. Develop solutions with production use in mind, partnering with Engineering and MLOps to integrate models into ML pipelines and support deployment, monitoring and ongoing improvement. Write tested, modular and maintainable Python and SQL, contributing ...

logistic regression, gradient boosting, random forests, clustering, NLP Proficient in Python and/or R, with strong experience in data quality, model development and feature engineering Strong command of SQL and familiarity with data engineering environments such as Databricks or similar Skilled in data visualisation and storytelling ...

grow and advance. Accenture's Data and AI practice covers the range of Data and AI skills, from Strategy, Data Science, Data Architecture, AI Engineering and Visual Insights. When combined with Accenture's broader Strategy and Consulting practice, we are able to bring together the unique ability to drive … capabilities that empower analytics and AI teams. Assist senior leaders in shaping elements of the strategic direction for practice's data science and data engineering ecosystem. Help assess generative AI proposals by reviewing feasibility, data requirements, model considerations, and integration with existing technology stacks. Collaborate with digital teams, architects ...

robust, ethical and useful. The role combines technical delivery, stakeholder collaboration and product-minded thinking.You will work with multidisciplinary teams across data, AI, software engineering, product, QA and delivery to create practical outcomes for clients and end users. Key responsibilities Lead the design, development, validation and deployment support … science models and analytical products. Apply advanced techniques such as machine learning, NLP, forecasting, optimisation or simulation where appropriate. Guide colleagues on data preparation, feature engineering, model selection, validation and interpretation. Work with data engineers and software teams to make data science outputs scalable, maintainable and usable. Communicate ...

Lead the development, implementation, and end-to-end delivery of advanced machine learning models and algorithms to drive market operations initiatives. Partner with AI Engineering teams to ensure robust architecture design and deployment patterns for AI/ML models that align with business needs. Mentor and guide a team … managing the machine learning lifecycle. Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn. Strong understanding of data preprocessing, feature engineering, and evaluation techniques. Experience working with large, complex datasets and applying statistical analysis. Familiarity with cloud platforms (AWS, Azure, GCP) and containerization ...

ensuring high-quality, scalable model delivery across fraud and transaction monitoring use cases. Driveend-to-end model lifecycle ownership — from data exploration and feature engineering to deployment, monitoring, and performance optimisation. Provide hands-on technical leadership, reviewing Python code, model design, distributed computing approaches, and architectural decisions. Manage ...

Schedule Full time Job Shift Day Job Description We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III – DevOps/AWS Engineer at JPMorganChase within the Commercial & Investment Bank, particularly in the Payments Technology … quality production code; review and debug code written by others to ensure reliability, performance, and maintainability. Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, accelerated test strategy, incident/root-cause ...

research-only environment. You'll work on real business problems, build machine learning models that drive decision-making, and collaborate closely with engineering teams to see your work deployed and used at scale. What you'll be doing: Partnering with stakeholders to turn business challenges into Data Science solutions … looking for: Commercial experience as a Data Scientist Strong Python and SQL skills Hands-on experience building Machine Learning models Expertise in feature engineering, model evaluation and model selection Experience working with large datasets Exposure to Azure, AWS or GCP Strong stakeholder management and communication skills Experience taking ...

models (not just consuming APIs) A solid understanding of model evaluation and validation, overfitting and bias/variance trade‐offs, and data quality and feature engineering Proficiency in Python and ML frameworks such as PyTorch or TensorFlow Experience building and maintaining ML pipelines in production Familiarity with ...

models (not just consuming APIs) • A solid understanding of model evaluation and validation, overfitting and bias/variance trade-offs, and data quality and feature engineering • Proficiency in Python and ML frameworks such as PyTorch or TensorFlow • Experience building and maintaining ML pipelines in production • Familiarity with ...

deep learning frameworks such as PyTorch, with openness to learning new tools and technologies. Practical experience across ML and LLM software stack, including feature engineering, model development, deployment, and validation. Prior experience working with omics data and familiarity with oncology drug development. Excellent communication skills, with the ability ...

Data Science team of a large, established financial services business. The company has invested in its data platform and is building a dedicated ML Engineering capability to get more models into production. You'll work on real business problems, using large and varied datasets to develop models that … initial experimentation. You should be comfortable with: Python and common data science libraries. SQL and working with large datasets. Statistical modelling and machine learning. Feature engineering, model selection and evaluation. Writing clear, maintainable and testable code. Git-based development workflows. Working in a cloud environment such as Azure ...

taking MLmodels from prototype through to production Strong experience with Google Cloud Platform, BigQuery and Vertex AI Strong Python and SQL skills Experience in feature engineering, statistical validation and modelevaluation Comfortable working with messy, imperfect real-world data rather than cleanbenchmark datasets Able to explain model outputs clearly ...

come beyond. Our UK customers can also save, invest and combine their pensions with us. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments … scales into new marketsshaping how advanced ML and AI can create real value in BorrowingYou'll partner closely with leaders across Credit Strategy, Product, Engineering, Model Validation, Data, and Platform, and influence decisions that shape both business performance and the long-term architecture of credit decisioning at Monzo. What ...