1 to 25 of 38 Permanent Feature Engineering Jobs in London

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 … Flow Have experience with agile delivery methodologies and CI/CD processes and tools Have a broad 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 More ❯

real-world problems, shipping results fast, all whilst meeting launch deadlines. Take ownership of end-to-end ML model development-from data preprocessing and feature engineering to training, testing, and deployment. Collaborate across teams to implement machine learning solutions into production systems, ensuring that models are scalable, reliable … machine learning, with a strong understanding of core ML algorithms and frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Hands-on experience with data preprocessing, feature engineering, and model training for real-world problems. Strong Python and Java programming skills and familiarity with NLP algorithms and libraries. Solid understanding More ❯

AI solutions across marketing and customer experience. What You'll Do Model & Build: Support the design and deployment of pragmatic machine learning solutions - from feature engineering in SQL to model development in Python, and deploying in production environments like AWS. Explore & Prototype: Help bring new ideas to life … to everything you do. Pace and impact matter here. What You'll Bring Must-Have: A degree in a STEM discipline (Computer Science, Maths, Engineering, etc.) or equivalent practical experience. 2-4 years of experience delivering DS/ML solutions in production environments - ideally in settings where you've … had to wear multiple hats (e.g., startups, small teams). Fluency in Python and SQL; experience building and deploying models end-to-end, from feature engineering to performance validation. Comfort with cloud tools (AWS preferred), Git, and CI/CD pipelines. Ability to work independently and juggle priorities More ❯

support commercial growth and enhance customer experiences and outcomes. Leading and supporting end-to-end data science projects, including business case development, solution design, feature engineering, model development, deployment, and MLOps. Taking ownership of existing ML/AI projects, including ongoing monitoring of model performance, data drift, scoring … support commercial growth and enhance customer experiences and outcomes. Leading and supporting end-to-end data science projects, including business case development, solution design, feature engineering, model development, deployment, and MLOps. Taking ownership of existing ML/AI projects, including ongoing monitoring of model performance, data drift, scoring More ❯

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 … 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 … 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 More ❯

PyTorch, or other relevant frameworks. Collaborate with cross-functional teams to integrate AI/ML solutions into our SaaS platform. Work on data preprocessing, feature engineering, and model optimization to ensure high accuracy and performance. Evaluate and fine-tune models to improve accuracy and performance. Integrate machine learning … in AI/ML and fintech trends to drive innovation within the company. Requirements: Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, Mathematics, or a related field. 3-5 years of professional experience in AI/ML development, preferably in fintech or a related More ❯

PyTorch, or other relevant frameworks. Collaborate with cross-functional teams to integrate AI/ML solutions into our SaaS platform. Work on data preprocessing, feature engineering, and model optimization to ensure high accuracy and performance. Evaluate and fine-tune models to improve accuracy and performance. Integrate machine learning … in AI/ML and fintech trends to drive innovation within the company. Requirements: Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, Mathematics, or a related field. 3-5 years of professional experience in AI/ML development, preferably in fintech or a related More ❯

then put into practice and become certified on various Cloud (and related) technologies that will help you to develop your own toolkit. Requirements Software Engineering: Proficiency in programming languages used in ML, such as Python/Java. Knowledge of software development best practices and methodologies. Experience with version control … learning principles, algorithms, and techniques. Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. Proficiency in data preprocessing, feature engineering, and model evaluation. Knowledge of ML model deployment and serving strategies, including containerization and microservices. Familiarity with ML lifecycle management, including versioning … in a similar role, with an excellent understanding of AI/ML lifecycle management. Strong experience deploying and productionising ML models. Familiarity with data engineering concepts, including data pipelines, ETL processes, and big data technologies. Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ More ❯

then put into practice and become certified on various Cloud (and related) technologies that will help you to develop your own toolkit. Requirements Software Engineering: • Proficiency in programming languages used in ML, such as Python/Java. • Knowledge of software development best practices and methodologies. • Experience with version control … learning principles, algorithms, and techniques. • Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. • Proficiency in data preprocessing, feature engineering, and model evaluation. • Knowledge of ML model deployment and serving strategies, including containerization and microservices. • Familiarity with ML lifecycle management, including versioning … in a similar role, with an excellent understanding of AI/ML lifecycle management. • Strong experience deploying and productionizing ML models. • Familiarity with data engineering concepts, including data pipelines, ETL processes, and big data technologies. • Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ More ❯

ideas and commitment to excellence, we want you to join us. To learn more visit alti-global.com. Job Description & Overview The Head of Data Engineering & Analytics will lead the development and execution of AlTi’s enterprise data engineering strategy, enabling the capture, transformation, storage and delivery of high … quality data across the firm’s global wealth, investment, corporate and asset management functions. This leader will architect and scale data engineering capabilities to support real-time and batch integration, reporting, and advanced analytics. This role reports to the CTO and will be a key member of the Global … Technology Solutions leadership team. In this hands-on leadership role, you will work at the intersection of data engineering, business intelligence, data science, strategy and governance. The ideal candidate will combine deep technical expertise in cloud data platforms and integration tools with strong experience implementing scalable data pipelines, robust More ❯

ideas and commitment to excellence, we want you to join us. To learn more visit alti-global.com. Job Description & Overview The Head of Data Engineering & Analytics will lead the development and execution of AlTi’s enterprise data engineering strategy, enabling the capture, transformation, storage and delivery of high … quality data across the firm’s global wealth, investment, corporate and asset management functions. This leader will architect and scale data engineering capabilities to support real-time and batch integration, reporting, and advanced analytics. This role reports to the CTO and will be a key member of the Global … Technology Solutions leadership team. In this hands-on leadership role, you will work at the intersection of data engineering, business intelligence, data science, strategy and governance. The ideal candidate will combine deep technical expertise in cloud data platforms and integration tools with strong experience implementing scalable data pipelines, robust More ❯

NLP tasks. Relationship Extraction: Evaluating different models for use-case specific RE, such as ATG. Document and text Classification Data Science: Data clustering algorithms, feature engineering Evaluate and integrate new technologies and models. Cross-team collaboration, identifying innovations and architecting solutions. Provide leadership and technical direction to various More ❯

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 … 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 … 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 More ❯

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 … 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). … 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 More ❯

subdomains like sentiment analysis or natural language understanding Proficiency in Python and relevant libraries (TensorFlow, PyTorch, Hugging Face, etc.) Strong understanding of machine learning engineering and software development Experience with data preprocessing, feature engineering, and model evaluation Experience in financial services industry What's In It For More ❯

subdomains like sentiment analysis or natural language understanding Proficiency in Python and relevant libraries (TensorFlow, PyTorch, Hugging Face, etc.) Strong understanding of machine learning engineering and software development Experience with data preprocessing, feature engineering, and model evaluation Experience in financial services industry What's In It For More ❯

for end-to-end Machine Learning Scientists that have a strong background and experience in machine learning pipeline going through business understanding, data exploration, feature engineering, model building, performance evaluation, testing and production deployment. Our Product Analytics team is at the heart of data-driven decision-making, empowering … partner closely with product managers and business leaders to uncover insights, measure impact, and drive strategy. By analysing player behaviour, identifying trends, and evaluating feature performance, our team ensures that every decision is informed by robust, actionable data. Together, we fuel innovation and help deliver personalised, engaging experiences that … are looking for people who can support our ethos. To apply to this post, you will have: MSc in Computer Science/Statistics/Engineering or a related field with a focus on applied statistics, AI, machine learning, or related fields with experience working with predictive and probabilistic models More ❯

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. More ❯

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 More ❯

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 … best practices, etc. so that they increase usage across a 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 More ❯

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 … 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 More ❯

Proficient in Python programming and SQL, with experience in production-level code and data analysis libraries. · Familiar with ML Ops, model development workflows, and feature engineering techniques. · Capable of manipulating data and developing models accessible for business use, with experience in Azure AI Search. · Adept with software development More ❯

Proficient in Python programming and SQL, with experience in production-level code and data analysis libraries. · Familiar with ML Ops, model development workflows, and feature engineering techniques. · Capable of manipulating data and developing models accessible for business use, with experience in Azure AI Search. · Adept with software development More ❯

on with innovative, composable tooling to prototype, iterate fast, and productionise what works. Stay up to date with emerging tech and practices in data engineering, analytics, and AI, advocating for thoughtful adoption. Evangelise data capabilities internally, supporting analysts, marketers, and operators in better leveraging the data platform. What you … the industry particularly from an AI perspective. A strong interest in the evolving AI landscape and experience supporting AI/ML use cases through feature engineering, model-ready data pipelines, or production data workflows. To be successful at Monica Vinader You are a doer You're a team More ❯

APIs, S3 buckets, web interfaces) in multiple formats. Develop programmatically validated data schemas and supporting documentation. Explore and recommend alternate technologies for enhanced data engineering solutions. Key Skills & Experience: 5+ years of relevant industry experience, ideally within financial services, capital markets, or asset management sectors. Proficient in Python … relational databases, validation, cleansing) and algorithms/data structures. Experienced in Agile development environments and test-driven development. Background working with geospatial data and feature engineering for machine learning applications. Good communicator, team player, with strong attention to detail and creativity. Desirable: Demonstrated portfolio of work (e.g., open More ❯