1 to 25 of 40 Remote Feature Engineering Jobs in London

Aimpoint Digital is a premier analytics consulting firm with a mission to drive business value for clients through expertise in data strategy, data analytics, decision sciences, and data engineering and infrastructure. This position is within our decision sciences practice which focuses on delivering solutions via machine learning and statistical modelling. What you will do As a part of Aimpoint … Become a trusted advisor working with clients to design end-to-end analytical solutions Work independently to solve complex data science use-cases across various industries Design and develop feature engineering pipelines, build ML & AI infrastructure, deploy models, and orchestrate advanced analytical insights Write code in SQL, Python, and Spark following software engineering best practices Collaborate with … impact for your clients and do so through thoughtfulness, prioritization, and seeing a solution through from brainstorming to deployment. In particular you have these traits: Degree in Computer Science, Engineering, Mathematics, or equivalent experience. Experience with building high quality Data Science models to solve a client's business problems Experience with managing stakeholders and collaborating with customers Strong written More ❯

developing and integrating cutting-edge AI solutions—including LLMs and AI agents —into our products and operations at a leading SaaS company. You’ll collaborate closely with product and engineering teams to deliver innovative, high-impact systems that push the boundaries of AI in rebate management. This is a highly collaborative and fast-moving environment where your contributions will … or in collaboration with other specialists. Optimize model pipelines for latency, scalability, and cost-efficiency, and support real-time and batch inference needs. Collaborate with MLOps, DevOps, and data engineering teams to ensure reliable model deployment and system integration. Stay informed on current research and emerging tools in LLMs, generative AI, and autonomous agents, and evaluate their practical applicability. … Participate in roadmap planning, design reviews, and documentation to ensure robust and maintainable systems. Required Qualifications 5+ years of experience in machine learning engineering, applied AI, or related fields. Bachelor’s or Master’s degree in Computer Science, Machine Learning, Engineering, or a related technical discipline. Strong foundation in machine learning and data science fundamentals—including supervised/ More ❯

features. Company Description Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change. By combining world-class engineering, industry expertise, and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and … expertise in Python-based AI/ML development, big data processing, and cloud-based AI platforms (Databricks, Azure ML, AWS SageMaker, GCP Vertex AI). Key Responsibilities Data Exploration & Feature Engineering Perform thorough Exploratory Data Analysis (EDA) and identify key variables, patterns, and anomalies. Engineer and select features for optimal model performance, leveraging domain understanding. Machine Learning & Statistical … skills, qualifications, and potential. If you need adjustments or support during the recruitment process, please let us know. Seniority level Mid-Senior level Employment type Full-time Job function Engineering and Information Technology Industries IT Services and IT Consulting #J-18808-Ljbffr More ❯

with advancements in machine learning, AI, and data science methodologies to continuously improve processes and solutions Requirements for the role Master’s or Ph.D. in Computer Science, Statistics, Mathematics, Engineering, or a related field (Bachelor’s with significant experience also considered) 3+ years of experience in data science, machine learning, or a related role Proficiency in programming languages such … R, and libraries like TensorFlow, PyTorch, Scikit-learn, or Pandas Strong understanding of statistical modeling, probability, and optimization techniques Ability to work with messy, real-world datasets and perform feature engineering Excellent problem-solving skills and attention to detail Strong communication skills to convey complex concepts to diverse audiences Bonus points You’ve worked in an early-stage More ❯

modeling, machine learning, and data mining techniques, with a focus on applications in text analysis or scientific data, including knowledge of forecasting, A/B testing, entity extraction, and feature engineering. Proficiency in programming languages such as Python, R, and SQL, and data analysis libraries (e.g., Pandas, NumPy, SciPy, Tidyverse). Strong knowledge of machine learning frameworks and libraries More ❯

Proficient: • Languages/Framework: Python, Fast API, Azure UI Search API (React) • Cloud: Azure Cloud Basics (Azure DevOps) • GitLab: GitLab Pipeline • Ansible and REX: Rex Deployment • Data Science : Prompt Engineering + Modern Testing • Data pipeline development and monitoring • Understanding of AI/ML algorithms and their applications • MLOps frameworks • Knowledge of cloud platforms (Azure ML especially) • Model deployment process … Storage Account, PostgreSQL, Cosmos o Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn) o Knowledge of cloud platforms (AWS SageMaker, Google AI Platform) o Expertise in data pre-processing, feature engineering, and model evaluation o Understanding of software engineering principles (version control, CI/CD, containerization) o Familiarity with distributed computing and big data tools (Spark, Hadoop More ❯

Proficient: • Languages/Framework: Python, Fast API, Azure UI Search API (React) • Cloud: Azure Cloud Basics (Azure DevOps) • GitLab: GitLab Pipeline • Ansible and REX: Rex Deployment • Data Science : Prompt Engineering + Modern Testing • Data pipeline development and monitoring • Understanding of AI/ML algorithms and their applications • MLOps frameworks • Knowledge of cloud platforms (Azure ML especially) • Model deployment process … Storage Account, PostgreSQL, Cosmos o Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn) o Knowledge of cloud platforms (AWS SageMaker, Google AI Platform) o Expertise in data pre-processing, feature engineering, and model evaluation o Understanding of software engineering principles (version control, CI/CD, containerization) o Familiarity with distributed computing and big data tools (Spark, Hadoop More ❯

latency, and compute constraints. Apply and innovate on methods like Bayesian neural networks , variational autoencoders , diffusion models , and Gaussian processes for modern AI use cases. Collaborate closely with product, engineering, and business teams to build end-to-end modeling solutions. Conduct deep-dive statistical and machine learning analyses, simulations, and experimental design. Stay current with emerging trends in generative … TensorFlow Probability , or similar probabilistic programming tools. Hands-on experience with classical ML and modern techniques, including deep learning , transformers , diffusion models , and ensemble methods . Solid understanding of feature engineering, dimensionality reduction, model construction, validation, and calibration. Experience with uncertainty quantification and performance estimation (e.g., cross-validation, bootstrapping, Bayesian credible intervals). Familiarity with database and data … processing tools (e.g., SQL, MongoDB, Spark, Pandas). Ability to translate ambiguous business problems into structured, measurable, and data-driven approaches. Preferred Qualifications: M.Sc or PhD in Statistics, Electrical Engineering, Computer Science, Physics, or a related field. Background in generative modeling , Bayesian deep learning , signal/image processing , or graph models . Experience applying probabilistic models in real-world 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! Seniority level Seniority level Mid-Senior level Employment type Employment type Contract Job function Job function Information Technology Industries Staffing and Recruiting Referrals increase More ❯

or data scientist, with a track record of leading successful AI projects Proficiency in AI and machine learning frameworks and programming languages (e.g., Python) Strong expertise in data preprocessing, feature engineering, and model evaluation Excellent problem-solving and critical-thinking skills Effective leadership, communication, and team management abilities A passion for staying at the forefront of AI and More ❯

improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for modelling, working closely with analytics engineering teams Contribute to the development of end-to-end machine learning workflows and help embed models into production … heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to explain complex findings clearly to both technical and non-technical More ❯

improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for modelling, working closely with analytics engineering teams Contribute to the development of end-to-end machine learning workflows and help embed models into production … heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to explain complex findings clearly to both technical and non-technical More ❯

and prospects' questions, based on knowledge of Acadian's processes and pertinent new research. Explore structured and unstructured datasets with a focus on data preparation, transformation, outlier detection, and feature engineering. Collaborate on the design of ESG constraints for client-driven investment solutions, help build predictive models and design interactive data applications. We're Looking for Teammates With: Bachelor 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 work on projects delivering to National Security customers, requiring the highest level of UK Security Vetting (DV) upon application. Key Responsibilities: You will blend Data … Engineering and Data Science, with experience covering tasks such as: Data Engineering tasks Manage integrations between data warehouse and other systems. Create deployable data pipelines using technologies like Nifi, Spark. Build analytics tools to provide insights into client requirements and operational metrics. Conduct onsite client visits and provide customer support. Problem-solve pragmatically, offering technical support and agile … and AI models. Design and deploy machine learning services accessible via APIs. Research and analyse data sets using statistical and machine learning techniques. Support analytical needs including data cleansing, feature engineering, and visualisation. Review software performance and establish key findings for business and clients. Assist the Business Development team with proposals and bids. The role offers genuine autonomy 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 ❯

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 ❯

trends and AI applications to enhance solution design What You'll Bring: 3+ years in a hybrid analytics and consulting role, ideally in healthcare Strong skills in data preparation, feature engineering, and model development Proficiency in SQL, Python, R, or similar languages Ability to create clear, engaging data visualisations for non-technical audiences Experience managing stakeholders and delivering … in fast-paced, deadline-driven settings Knowledge of the UK healthcare landscape and its challenges A degree in engineering, mathematics, statistics, or a related field Why Join? Shape healthcare outcomes with cutting-edge AI and analytics Enjoy a flexible hybrid model and up to 2 months of remote work annually Access private medical insurance for prompt, personalised care Thrive … Editor, Fashion Buying (Fixed-Term) London, England, United Kingdom 2 days ago S/4 Finance Transformation Manager/Senior Manager London, England, United Kingdom 2 weeks ago Pharmaceutical Engineering - KTP Associate Harlow, England, United Kingdom 2 weeks ago Enfield, England, United Kingdom 3 days ago Defence Children Services (DCS)-Teacher of Science (with Biology KS5)- King Richard School More ❯

be considered for this position. ABOUT THIS OPPORTUNITY A great opportunity has arisen for a Data Engineer to work within the Personalised Experiences and Communications Platform to join product engineering cross-functional teams. As a Data Engineer, your responsibilities will be delivering the highest quality data capability, drawing upon your engineering expertise, whilst being open-minded to the … opportunities the cloud provides. What you’ll be doing... Building reusable data pipelines at scale, working with structured and unstructured data, and feature engineering for machine learning or curating data to provide real-time contextual insights to power our customers' journeys. Using industry-leading toolsets, as well as evaluating exciting new technologies to design and build scalable real … Azure, Teradata, SQL Server) you’ll get to work building capabilities with horizon-expanding exposure to a host of wider technologies and careers in data. Helping in adopting best engineering practices like Test Driven Development, code reviews, Continuous Integration/Continuous Delivery, etc., for data pipelines. Mentoring other engineers to deliver high-quality and data-led solutions for our More ❯

at scale to help optimise product bidding and maximise profit across platforms like Google Shopping. Expect to work across the full ML lifecycle—from exploring large, messy datasets and engineering features, to evaluating models offline and running experiments to validate impact. At the same time, you'll build, deploy and monitor models in production: setting up retraining workflows, pipeline … clean, documented, well tested and reviewed code and have tooling and a culture to support this. This is a hands-on, high-impact role that blends research, experimentation and engineering, all tied to clear business outcomes. You'll collaborate closely with marketers, data analysts and engineers, and play a key part in shaping the future of how we scale … at scale to help optimise product bidding and maximise profit across platforms like Google Shopping. Expect to work across the full ML lifecycle—from exploring large, messy datasets and engineering features, to evaluating models offline and running experiments to validate impact. At the same time, you'll build, deploy and monitor models in production: setting up retraining workflows, pipeline More ❯

be doing: Designing and maintaining scalable data pipelines and infrastructure to support structured, analysis-ready data Designing and deploying end-to-end machine learning models from data preparation and feature engineering to model training, evaluation, and monitoring Overseeing a team of three data analysts and collaborating closely with business analysis and developers across William Reed Setting out a More ❯

be doing: Designing and maintaining scalable data pipelines and infrastructure to support structured, analysis-ready data Designing and deploying end-to-end machine learning models from data preparation and feature engineering to model training, evaluation, and monitoring Overseeing a team of three data analysts and collaborating closely with business analysis and developers across William Reed Setting out a More ❯

and a clear path for continued growth, they are now hiring a Data Engineer to support their next generation of products and data initiatives. Reporting to the VP of Engineering Operations, this role will focus on building scalable data systems and integrating machine learning workflows that drive real-time personalisation and business insights across a high-traffic platform. Key … Responsibilities Design, build, and maintain robust data pipelines (batch and real-time)* Integrate and monitor machine learning models within live data workflows* Collaborate with Engineering, Product, and Analytics to ensure data accessibility and reliability* Optimise data infrastructure and automate manual processes* Uphold data integrity with strong validation and testing practices* Drive improvements in data delivery, observability, and internal tooling … cross-functional teams in leveraging data for decision-making Ideal Candidate Strong proficiency in Python and SQL for data wrangling and automation* Experience with ML workflows, model deployment, and feature engineering* Familiarity with modern data platforms (e.g., BigQuery, dbt, Looker)* Understanding of data modelling and cloud-based infrastructure (AWS or GCP)* Comfortable working in a fast-paced, product More ❯

emerging technologies, industry trends, and best practices , ensuring the data platform remains cutting-edge. Key Skills & Experience 10+ years of experience in data architecture, solution architecture, or cloud data engineering , with a focus on data platform strategy and leadership . Proven experience leading and mentoring teams in data platform architecture and solution design. Deep expertise in Azure data services … MDM, data governance, and data quality tools . Experience designing and integrating Machine Learning (ML) architectures on Azure , including: MLOps and model lifecycle management in Azure ML and Databricks Feature engineering and feature stores in a cloud-based data ecosystem Model deployment, serving, and monitoring within a Lakehouse or Data Mesh framework. Proficiency in Apache Spark, Python 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 ❯