51 to 75 of 77 Feature Engineering Jobs in the UK

drive innovation into the product development process. You will interpret your client’s objectives, desires, and preferences to help the wider technical team understand the opportunities and apply data engineering responsibilities consistently. You will be working on an interesting range of projects that deliver to National Security customers and as such, you will have to hold the highest level … of UK Security Vetting (DV), upon application. Key Responsibilities: You will blend Data Engineering and Data Science, and will have experience that might cover a number of the tasks listed below: Data Engineering tasks Manage the implementation and development of integrations between the data warehouse and other systems. Create deployable data pipelines that are tested and robust using … Research, analyse and apply data sets using a variety of statistical and machine learning techniques. Support the analytical needs of the technical team inclusive of cleansing, mapping, statistical inferences, feature engineering and the bespoke data visualisation methods required by each project. Review the execution of software solutions and how these perform for the business and your clients, establishing More ❯

drive innovation into the product development process. You will interpret your client’s objectives, desires, and preferences to help the wider technical team understand the opportunities and apply data engineering responsibilities consistently. You will be working on an interesting range of projects that deliver to National Security customers and as such, you will have to hold the highest level … of UK Security Vetting (DV), upon application. Key Responsibilities: You will blend Data Engineering and Data Science, and will have experience that might cover a number of the tasks listed below: Data Engineering tasks Manage the implementation and development of integrations between the data warehouse and other systems. Create deployable data pipelines that are tested and robust using … Research, analyse and apply data sets using a variety of statistical and machine learning techniques. Support the analytical needs of the technical team inclusive of cleansing, mapping, statistical inferences, feature engineering and the bespoke data visualisation methods required by each project. Review the execution of software solutions and how these perform for the business and your clients, establishing More ❯

Qualifications: PhD in a relevant discipline or Master’s plus a comparable level of experience Experience in Knowledge Graphs or Large Document Search Experience with traditional ML models and feature engineering. Strong Experience with fine tuning, modelling and deploying LLMs - experience with RAG, IR, NER etc would also be very beneficial Strong programming skills (e.g., Python) and experience with … modern ML frameworks (e.g., PyTorch, TensorFlow, LangChain). Collaborating with other Researchers, Product, Engineering and Business Stakeholders in an agile manner to demonstrate value and iterate with customer feedback. Please apply below for immediate consideration More ❯

Qualifications: PhD in a relevant discipline or Master’s plus a comparable level of experience Experience in Knowledge Graphs or Large Document Search Experience with traditional ML models and feature engineering. Strong Experience with fine tuning, modelling and deploying LLMs - experience with RAG, IR, NER etc would also be very beneficial Strong programming skills (e.g., Python) and experience with … modern ML frameworks (e.g., PyTorch, TensorFlow, LangChain). Collaborating with other Researchers, Product, Engineering and Business Stakeholders in an agile manner to demonstrate value and iterate with customer feedback. Please apply below for immediate consideration More ❯

grow by tackling complex technical challenges. Responsibilities Design, build, and maintain AI systems and tools using machine learning and large language models (LLMs), with a strong focus on prompt engineering and model fine-tuning. Collaborate with cross-functional teams to identify opportunities for AI and automation across the product suite. Develop scalable pipelines for data ingestion, model training, evaluation … operating as a senior level engineer within a product or SaaScompany Proven experience with Python and ML libraries such as TensorFlow or PyTorch. Experience working with LLMs (Gemini), prompt engineering, and reinforcement learning from human feedback (RLHF). Experience with LangChain for building LLM applications with RAG pipelines and agent workflows. Practical understanding of vector search, embeddings, and retrieval … generation (RAG). Experience building and deploying machine learning models into production environments. Familiarity with MLOps tools and practices (Vertex AI). Understanding of data pipelines, data preparation, and feature engineering. Bonus Points for: Hands-on experience with prompt tuning, fine-tuning LLMs, or adapting open-source models for specific use cases. Hands-on experience with AlloyDB or similar. More ❯

of data scientists, helping refine their workflows and ensure high-quality deliverables. You will: Lead and mentor a team of data scientists in building predictive models. Oversee data cleaning, feature engineering, and model development pipelines. Build and maintain robust, scalable linear regression and statistical models for KPI forecasting. Drive improvements in internal tooling and API integrations. Collaborate closely … with leadership, engineering, and the revenue team to translate business needs into data science solutions. Play a key role in product innovation, helping shape how new data products are designed and delivered. What They're Looking For 5+ years’ experience in data science or a closely related field. Proven leadership experience — mentoring or managing junior data scientists. Expert Python More ❯

and analytics Clear and confident communication skills (written and verbal) A blend of technical know-how and creativity in model development A curious, investigative mindset to explore and test feature engineering techniques Excellent attention to detail and data quality Ability to work both independently and collaboratively in a team environment Proficiency in R Solid knowledge of SQL Working More ❯

the scale it takes for us to feed the nation. The level of data, transactions and variety it involves. Then you'll realise that ours is a modern software engineering environment because it has to be. We've made serious investment into a Tech Academy and into setting standards and principles. We iterate, learn, experiment and push ways of … in everything from AI to reusable tech. Joining Sainsbury's Tech means becoming part of an inclusive and driven team that is passionate about creating innovative solutions. As an Engineering Manager, you will play a pivotal role in leading and coaching talented engineering teams, driving the delivery of impactful solutions that drive efficiency and enhance performance across the … business. With a focus on continuous improvement, you will have the opportunity to shape a world-class engineering function and contribute to the development of cutting-edge processes and technologies. At Sainsbury's, we value collaboration, diversity, and inclusivity, and offer a supportive and inspiring environment where you can make a purposeful contribution. Join us to be a part More ❯

Machine Learning Engineering Manager (Operations) Join to apply for the Machine Learning Engineering Manager (Operations) role at THG Ingenuity . About THG Ingenuity THG Ingenuity is a fully integrated digital commerce ecosystem, designed to power brands without limits. Our global end-to-end tech platform includes three products: THG Commerce, THG Studios, and THG Fulfilment. Each offers a … goals. Oversee the entire lifecycle of ML projects from conception to deployment and monitoring. Guide the team in building, training, and deploying models. Ensure best practices in data preparation, feature engineering, and model validation. Establish workflows for deployment, monitoring, and scaling of models. Qualifications Proven experience as a Machine Learning Engineer, with leadership experience in deploying models in More ❯

We are seeking a seasoned Principal Engineer to lead the design, development, and evolution of our Observability Platform , ensuring it meets the needs of our rapidly scaling systems and engineering teams. This role will also focus on leveraging Machine Learning (ML) and Artificial Intelligence (AI) to deliver advanced insights that proactively improve system health and drive down Mean Time … the development and adoption of platform capabilities to ensure system health, reliability, and performance. Establish and evolve platform standards and best practices to align with the company's overall engineering goals. Strategic Initiatives Collaborate with engineering teams to define the observability strategy, ensuring alignment with business and operational objectives. Identify and integrate the latest observability technologies, including AI … performant, and secure across all environments. Optimize data collection, processing, and storage to balance performance with cost efficiency. Define SLAs, SLOs, and SLIs for observability services to support reliability engineering practices. Continuously improve MTTD and MTTR by leveraging advanced AI/ML models for predictive analysis and automated responses. Mentorship and Collaboration Act as a mentor and technical leader More ❯

skills – even better if these skills have been applied to threat detection, malware analysis, phishing and/or abuse detection. Experience building production-grade AI pipelines, including data ingestion, feature engineering, validation, model deployment, and monitoring. Experience designing and implementing anomaly detection, classification, clustering, and retrieval across vision and language models, ideally for identifying cyber threats (URLs, domains … fit to problem space, including scenarios where RAG is applicable. Incident response experience, and ability to work with large, noisy, and rapidly evolving threat datasets. Strong background in cloud engineering and containerisation (Docker, Kubernetes) with experience deploying AI services at scale, particularly on AWS via Terraform. The package offered to the Senior/Principal AI Engineer will consist of More ❯

skills – even better if these skills have been applied to threat detection, malware analysis, phishing and/or abuse detection. Experience building production-grade AI pipelines, including data ingestion, feature engineering, validation, model deployment, and monitoring. Experience designing and implementing anomaly detection, classification, clustering, and retrieval across vision and language models, ideally for identifying cyber threats (URLs, domains … fit to problem space, including scenarios where RAG is applicable. Incident response experience, and ability to work with large, noisy, and rapidly evolving threat datasets. Strong background in cloud engineering and containerisation (Docker, Kubernetes) with experience deploying AI services at scale, particularly on AWS via Terraform. The package offered to the Senior/Principal AI Engineer will consist of More ❯

skills – even better if these skills have been applied to threat detection, malware analysis, phishing and/or abuse detection. Experience building production-grade AI pipelines, including data ingestion, feature engineering, validation, model deployment, and monitoring. Experience designing and implementing anomaly detection, classification, clustering, and retrieval across vision and language models, ideally for identifying cyber threats (URLs, domains … fit to problem space, including scenarios where RAG is applicable. Incident response experience, and ability to work with large, noisy, and rapidly evolving threat datasets. Strong background in cloud engineering and containerisation (Docker, Kubernetes) with experience deploying AI services at scale, particularly on AWS via Terraform. The package offered to the Senior/Principal AI Engineer will consist of More ❯

with a strong analytical background, capable of maintaining technical contributions while managing a team. Your qualifications include: Experience delivering data science initiatives from concept to production, including data preprocessing, feature engineering, and model evaluation. Strong communication skills for explaining complex concepts to business stakeholders. Proficiency in Python or similar tools, strong SQL skills, and experience with data visualization More ❯

clustering, and retrieval across vision and language models, ideally for identifying cyber threats (URLs, domains, phishing, botnets, etc.) Hands-on experience building production -grade AI pipelines, including data ingestion, feature engineering, validation, model deployment, and monitoring . Proficient in a major backend language and related ML/AI libraries (e.g. Tensorflow & PyTorch , etc), with a preference for Go. … to problem space , including scenarios where RAG is applicable. Incident response experience, and ability to work with large, noisy, and rapidly evolving threat datasets . Strong background in cloud engineering and containerisation (Docker, Kubernetes ), with experience deploying AI services at scale, particularly on AWS via Terraform . Bonus points if you have: Experience with P erl . Experience leveraging More ❯

fairer credit system. The Role We're looking for an experienced MLOps Engineer for a 3-month contract to lead the development of our ML deployment, testing, monitoring, and feature engineering pipelines . You'll be responsible for establishing best practices and production-grade systems to support our machine learning workflows from training to deployment and beyond. The … pipeline using AWS , with a strong focus on SageMaker for training, deployment, and hosting. - Integrate and operationalize MLflow for model versioning, experiment tracking, and reproducibility. - Architect and implement a feature store strategy for consistent, discoverable, and reusable features across training and inference environments (e.g., using SageMaker Feature Store , Feast, or custom implementation). - Work closely with data scientists … to formalize feature engineering workflows , ensuring traceability, scalability, and maintainability of features. - Develop unit, integration, and data validation tests for models and features to ensure stability and quality. - Establish model monitoring and alerting frameworks for real-time and batch inference (e.g., model drift detection, performance degradation). - Build CI/CD pipelines for ML workflows (training, evaluation, deployment More ❯

choices. Follow best practices for ML experimentation and MLOps. PhD in a relevant discipline or Master s plus a comparable level of experience Experience with traditional ML models and feature engineering. Strong programming skills (e.g., Python) and experience with modern ML frameworks (e.g., Collaborating with other Researchers, Product, Engineering and Business Stakeholders in an agile manner to demonstrate More ❯

packaging and execution. Building out our offering around data modeling. You won't just work on the data models themselves - you'll work closely with Product and the wider Engineering team to shape the way we collect data via our trackers to build better data models, and drive what data model tooling we provide as part of our commercial … batch and streaming data processing . You have experience building streaming pipelines using tools like Benthos , enabling real-time data ingestion, transformation, and delivery across various systems. You understand feature engineering and management. You're familiar with tools like Feast for defining, materializing, and serving features in both real-time and batch contexts. You have extensive experience using … Python which is used for auto generating data models. You are not new to engineering . You use CI/CD, and Git source control as part of your daily job. You have experience with testing frameworks. You are a proactive learner . Eager to expand on your software engineering knowledge and adapt to new technologies essential for More ❯

What you will do In this role, you will provide technical leadership in the development of our Causal AI platform, guiding both the vision and execution within our Product Engineering team, which includes software engineers, data scientists, and machine learning experts. While you will actively contribute to coding and algorithm development, you will also play a pivotal role in … on: Leading the design and development of advanced Causal AI algorithms, with a focus on time series and tabular data, ensuring they are optimised for scalability and performance. Overseeing feature engineering and machine learning initiatives to deliver robust, production-quality solutions. Providing mentoring and technical guidance to junior engineers and data scientists, fostering a culture of continuous learning … product management, DevOps, and UX/UI design, to seamlessly integrate Causal AI capabilities into our platform's architecture. A minimum of 5 years of experience in machine learning engineering or a related field, with demonstrated success in deploying machine learning models into production environments. Strong academic background in a quantitative discipline (e.g., machine learning, statistics, mathematics) or equivalent More ❯

Key Responsibilities : Lead the development and maintenance of credit risk and affordability models using bureau, open banking, and alternative behavioural data. Own end-to-end model lifecycle: data sourcing, feature engineering, model development, validation, and monitoring. Design and execute champion/challenger tests and A/B experiments to continuously improve approval rates, loss rates, and customer experience … performance data to generate actionable insight and support strategic decisions Mentor and develop a small team of analysts/data scientists as the team scales Work closely with Data Engineering to deploy models into production pipelines. Collaborate with stakeholders to define modeling goals and interpret model outcomes in a business context. Requirements: 5-7 years of experience in consumer … using libraries like scikit-learn, XGBoost, or LightGBM. Strong experience working with transactional datasets (e.g., Open Banking and Categorisation) and bureau data (e.g., Experian, Equifax). Deep understanding of feature engineering, data preprocessing, and dealing with class imbalance. Ability to evaluate models using appropriate metrics (e.g., AUC, KS, precision/recall) and validate across multiple segments. Familiarity with More ❯

data in data lakehouses, but only leverage a fraction of it for predictive tasks. This is because traditional machine learning is slow and time consuming, taking months to perform feature engineering, build training pipelines, and achieve acceptable performance. At Kumo, we are building a machine learning platform for data lakehouses, enabling data scientists to train powerful Graph Neural … use our product, best practices, etc. so that they increase usage across a larger and larger number of internal workloads. Provide market and customer feedback to the Product and Engineering team to refine feature specifications and the product roadmap. Create broader processes for each customer to go through to ensure we can drive repeatable successes in PoCs. Generate More ❯

outright risk pricing or other product structures. Principal Responsibilities Modelling : Design and develop models to assist in alpha generation. Areas include: Automated evaluation of signal performance over time and feature engineering techniques to drive improvements. Combination of multiple signals to produce a single useable alpha for different contexts and attribution of performance. Robust estimation of key metrics such More ❯

their Research & Development team. You will play a key role in enhancing and developing state-of-the-art sports models. This position sits at the intersection of data science, engineering, software development, and mathematics , offering the opportunity to work on highly impactful machine learning solutions within the iGaming industry. Key Responsibilities Build and maintain robust, high-quality datasets for … Qualifications Solid experience with machine learning , particularly with neural networks . Strong programming skills, preferably in Python ; knowledge of Matlab is a plus. Expertise in data shaping, preprocessing, and feature engineering . Excellent command of English , both written and spoken. Prior experience in the iGaming or sports modelling industry is a strong advantage. What’s on Offer A More ❯

record of transitioning research into production. Proven team leadership in a technical or research setting. Expert in Python and PyTorch; JAX is a plus. Strong foundation in data preparation, feature engineering, and model evaluation. Excellent communicator with the ability to adapt messaging for different audiences. Strategic mindset and leadership potential at the executive level. Desirable: Background in analog … or general electronic engineering is a bonus. Experience with high-performance or low-latency ML systems. If you’re a principle machine learning engineer/team leader, or hold the relevant experience and are interested in this exciting opportunity, please do apply! If you are interested in another other AI/ML and Computer vision roles, please reach out More ❯

You have experience optimising solution performance with a constrained set of technologies. You have experience or are keen to engage with productionising machine learning technologies combined with large scale feature engineering. More ❯