1 to 25 of 41 Permanent Feature Engineering Jobs in London

an innovative team shaping next-generation solutions in the Telecoms sector. Key Responsibilities - Design, build and deploy AI/ML models, including LLMs and generative AI - Perform data exploration, feature engineering, and model optimisation - Apply supervised, unsupervised, and reinforcement learning algorithms - Conduct large-scale data analysis across structured and unstructured sources - Develop statistical and predictive models to drive 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 ❯

machine learning and deep learning models. Contribute to scalable and reusable data pipelines using modern ML workflows. Conduct experiments and benchmarking exercises to test model performance. Perform error analysis, feature importance, and other model diagnostics. Track and log training/testing outcomes to support reproducibility and model versioning. Engineering Contributions Help build and integrate AI-powered APIs, scripts … tools, and containerization (e.g., Docker) to maintain codebase quality. Applied AI Domains Work on projects involving Natural Language Processing (NLP), Computer Vision, Generative AI, or Recommendation Systems. Support annotation, feature engineering, and augmentation tasks where necessary. Write clear, well-organized documentation for code, models, datasets, and workflows. Participate in team meetings, sprint planning, and code reviews. Engage with … to reflect on progress, set learning goals, and track outcomes. Required Qualifications A Bachelor's or Master's degree (completed or ongoing) in Computer Science, Data Science, Mathematics, Software Engineering, or a related STEM field. Eligibility to enroll in a Level 6 or Level 7 AI/ML/Data Science apprenticeship programme. Core Skills & Competencies Technical Skills Programming More ❯

and deliver NLP based machine learning systems at scale that drive measurable impact for our business Own the full end to end machine learning delivery lifecycle including data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployments and maintenance Partner with stakeholders to propose innovative data products that leverage Trainline's extensive datasets and state … and platforms like ML Flow Have experience with agile delivery methodologies and CI/CD processes and tools Have a broad of understanding of data extraction, data manipulation and feature engineering techniques Are familiar with statistical methodologies. Have good communication skills Nice to have Experience with LangGraph or LangChain Experience with transport industry and/or geographical information More ❯

managers Design and deliver machine learning systems at scale that drive measurable impact for our business Own the full end to end machine learning delivery lifecycle including data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployments and maintenance Partner with stakeholders to propose innovative data products that leverage Trainline's extensive datasets and state … and foster a culture of rigorous learning and experimentation We'd love to hear from you if you Have a broad of understanding of data extraction, data manipulation and feature engineering techniques Are familiar with statistical methodologies Are skilled in one of reinforcement learning, predictive modelling (classification and regression) and have a solid understanding of recommendation systems Are More ❯

with different machine learning techniques and algorithms, including supervised, unsupervised, semi-supervised, reinforcement, and deep learning; Design and optimize machine learning pipelines and workflows, incorporating techniques for data cleaning, feature engineering, model selection, and hyperparameter tuning; and Develop scalable and efficient machine learning infrastructure and systems for training, testing, and deploying models in production environments. Qualifications Bachelor's More ❯

strong emphasis on mutual assistance. Each team member is approachable and committed to lending a hand, creating an environment where everyone feels supported and valued." - Sreekant, VP of API Engineering The team you'll work with: Reporting to the Director of AI, this is a high-impact role where your expertise will directly shape the future of our ML … value by: Model Development & Deployment: Develop, test, deploy, and maintain machine learning models and algorithms, ensuring their scalability, robustness, and performance in production. Data Analysis & Optimization: Conduct data preprocessing, feature engineering, and exploratory analysis to optimize AI/ML models. Pipeline Development & Enhancement: Design, build, and enhance efficient machine learning pipelines, ensuring their scalability and performance. Collaboration & Cross … technologies in data science and machine learning to identify new opportunities and techniques. To be a successful match you must have: 1+ years in a Machine Learning or ML Engineering role, with hands-on experience in deep learning frameworks (e.g., TensorFlow, PyTorch). Motivated recent graduates are encouraged to apply! A degree in Mathematics, Engineering, Statistics, Computer Science More ❯

SageMaker (moving to Azure ML); containerise code and hook into CI/CD. Monitoring & tuning - track drift, response quality and spend; implement automated retraining triggers. Collaboration - work with Data Engineering, Product and Ops teams to translate business constraints into mathematical formulations. Tech stack Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow) SQL (Redshift, Snowflake or similar) AWS SageMaker → Azure … clean, tested code. Cloud ML: hands-on with AWS SageMaker plus exposure to Azure ML; Docker, Git, CI/CD, Terraform. SQL mastery for heavy-duty data wrangling and feature engineering. Experimentation chops - offline metrics, online A/B test design, uplift analysis. Production mindset: containerise models, deploy via Airflow/ADF, monitor drift, automate retraining. Soft skills: clear More ❯

SageMaker (moving to Azure ML); containerise code and hook into CI/CD. Monitoring & tuning - track drift, response quality and spend; implement automated retraining triggers. Collaboration - work with Data Engineering, Product and Ops teams to translate business constraints into mathematical formulations. A typical day Morning stand-up: align on performance targets and new constraints. Data dive: explore panel behaviour … clean, tested code. Cloud ML: hands-on with AWS SageMaker plus exposure to Azure ML; Docker, Git, CI/CD, Terraform. SQL mastery for heavy-duty data wrangling and feature engineering. Experimentation chops - offline metrics, online A/B test design, uplift analysis. Production mindset: containerise models, deploy via Airflow/ADF, monitor drift, automate retraining. Soft skills: clear More ❯

We work closely with stakeholders across the business to expand the understanding and impact of machine learning and AI throughout Trainline. The Role We are looking for a MLOps Engineering Manager to join our team and help shape the future of train travel. You will be part of a highly innovative AI and ML team working alongside engineers, scientists … the opportunity to work with fellow ML enthusiasts on large-scale production systems, delivering highly impactful products that make a difference to our millions of users. As a MLOps Engineering Manager at Trainline you will Build a new team of MLOps Engineers working alongside ML Engineers, Data Engineers, Software Engineers, Data Scientists and Product Managers Define MLOps processes and … machine learning products Ensure delivery of high-quality, scalable and maintainable machine learning models and AI Systems that drive measurable impact for our business Act as a bridge between engineering and data, ensuring engineering standards are met while understanding the specificities of data, AI and machine learning challenges Take an active part in our AI and ML community More ❯

AI solutions that are scalable, reliable, and innovative. Key Responsibilities Develop, train, and deploy machine learning and deep learning models for production use. Collaborate on data collection, processing, and feature engineering for AI pipelines. Build scalable APIs and services to deliver AI capabilities within Magentic's products. Optimize model performance for speed, accuracy, and efficiency in real-world … scenarios. Stay current on the latest AI research and bring new ideas into our tech stack. Contribute to engineering best practices, code reviews, and technical documentation. What We're Looking For 3+ years of experience working on AI/ML systems in production environments. Proficiency in Python and ML frameworks like TensorFlow, PyTorch, scikit-learn. Experience designing and deploying … models using cloud platforms (AWS, GCP, or Azure). Solid understanding of data structures, algorithms, and software engineering principles. Experience with APIs, data pipelines, and model-serving infrastructure. Strong problem-solving and communication skills; ability to work cross-functionally. More ❯

to learn, teach, and ultimately, produce high quality results. Execute data analysis and exploratory analysis (project design, processing of and cleaning of data, merging/joining disparate data sources, feature engineering, performing analyses and communicating results). Produce models using a variety of algorithms (GLM, GBM, Random Forest, Neural Networks etc.) and assess the relative strength of each More ❯

and tools to improve investment processes and support deal teams. Support live due diligence by translating complex data into comprehensive analysis under tight deadlines. Perform advanced data analysis, including feature engineering and modeling. Cleanse, integrate, and analyze diverse datasets for insights. Conduct hypothesis testing, statistical analysis, and modeling. Create and manage a roadmap for analysis improvements and new … innovative data tools to scale deal support capabilities. Qualifications Education & Certificates Bachelor's degree or higher in a STEM field required. Concentration in Computer Science, Math, Physics, or related engineering field preferred. Professional Experience Minimum 6 years in data engineering or related fields, with proven success. Experience in consulting, investment banking, or client-focused roles is advantageous. Experience More ❯

success criteria. Support and mentor junior team members, fostering a collaborative environment. Independently manage client relationships and project expectations. Develop and deploy ML models, applying innovative approaches beyond basic feature engineering. Use Python, SQL, and Tableau for reporting and analysis within an AWS environment. Work closely with Data Engineering, Sales, and Market Research teams across the UK, US … meaningful insights to drive business decisions. Strong communication skills, with experience in managing client relationships. A degree in a relevant field such as Mathematics, Statistics, Economics, Psychology, Sociology, Physics, Engineering, or Computer Science (Master’s or PhD is a plus). Interest or experience in TV viewing data, media, or marketing analytics is beneficial but not essential. If this More ❯

success criteria. Support and mentor junior team members, fostering a collaborative environment. Independently manage client relationships and project expectations. Develop and deploy ML models, applying innovative approaches beyond basic feature engineering. Use Python, SQL, and Tableau for reporting and analysis within an AWS environment. Work closely with Data Engineering, Sales, and Market Research teams across the UK, US … meaningful insights to drive business decisions. Strong communication skills, with experience in managing client relationships. A degree in a relevant field such as Mathematics, Statistics, Economics, Psychology, Sociology, Physics, Engineering, or Computer Science (Master’s or PhD is a plus). Interest or experience in TV viewing data, media, or marketing analytics is beneficial but not essential. If this More ❯

reshaping credit from the inside out. About the Role As a Senior Data Scientist, you’ll take ownership across the full lifecycle of model development —from data wrangling and feature engineering to building and deploying ML models in production. Your work will directly power business decisions across underwriting, fraud detection, and customer conversion . This is a hands More ❯

reshaping credit from the inside out. About the Role As a Senior Data Scientist, you’ll take ownership across the full lifecycle of model development —from data wrangling and feature engineering to building and deploying ML models in production. Your work will directly power business decisions across underwriting, fraud detection, and customer conversion . This is a hands More ❯

Full-time | Hybrid Join a tech consultancy at the forefront of applied AI—helping global brands design and deploy intelligent systems that solve real business problems. They combine deep engineering know-how with domain expertise to build the data infrastructure that powers machine learning and generative AI at scale. 🔍 About the Role As a Lead Data Engineer , you’ll … platforms using tools like Databricks , Airflow , Snowflake , and Spark Collaborate with AI/ML teams to align data processing with model requirements Develop ETL/ELT workflows to support feature engineering, model training, and inference Optimise data workflows for scalability, reliability, and cost-efficiency Ensure security, compliance, and data governance standards (e.g. GDPR , RBAC) Mentor junior engineers and More ❯

Full-time | Hybrid Join a tech consultancy at the forefront of applied AI—helping global brands design and deploy intelligent systems that solve real business problems. They combine deep engineering know-how with domain expertise to build the data infrastructure that powers machine learning and generative AI at scale. 🔍 About the Role As a Lead Data Engineer , you’ll … platforms using tools like Databricks , Airflow , Snowflake , and Spark Collaborate with AI/ML teams to align data processing with model requirements Develop ETL/ELT workflows to support feature engineering, model training, and inference Optimise data workflows for scalability, reliability, and cost-efficiency Ensure security, compliance, and data governance standards (e.g. GDPR , RBAC) Mentor junior engineers and More ❯

leveraging approaches that optimize Amazon's systems using cutting edge quantitative techniques. The right candidate needs to be fluid in: Data warehousing and EMR (Hive, Pig, R, Python). Feature extraction, feature engineering and feature selection. Machine learning, causal inference, statistical algorithms and recommenders. Model evaluation, validation and deployment. Experimental design and testing. BASIC QUALIFICATIONS - 8+ 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 ❯

marketing and customer experience. What You'll Do Support the development of predictive models and data-driven solutions that solve real marketing and customer problems. Conduct exploratory data analysis, feature engineering, and data cleaning to prepare data for modelling. Write clean, well-documented Python and SQL code to support analysis and model development. Collaborate with other data scientists 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 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 ❯