1 to 25 of 47 Feature Engineering Jobs in London

this role.\ NOur Solutions & AI Labs (SAIL) practice is looking for an experienced Senior Manager to lead consultancy engagements and grow our AI & Solutions Engineering capability.\ NThe Forward Deployed AI & Solutions Engineer role will lead the delivery of AI-enabled solutions embedded in our clients' teams, combining deep technical … solutions directly embedded into business processes. We support clients across a number of industries and offer deep expertise in AI/ML, Cloud, Platform Engineering, and Managed Solutions. \ NWhat you will be doing \ NAs a Senior Manager in SAIL, you will own and lead consultancy engagements ...

role. \n Our Solutions & AI Labs (SAIL) practice is looking for an experienced Senior Manager to lead consultancy engagements and grow our AI & Solutions Engineering capability. \n The Forward Deployed AI & Solutions Engineer role will lead the delivery of AI-enabled solutions embedded in our clients' teams, combining deep … solutions directly embedded into business processes. We support clients across a number of industries and offer deep expertise in AI/ML, Cloud, Platform Engineering, and Managed Solutions. \n What you will be doing \n As a Senior Manager in SAIL, you will own and lead consultancy engagements ...

about leveraging cutting‐edge AI to transform financial markets? Do you thrive on building end‐to‐end solutions, from robust data pipelines and sophisticated feature engineering to deploying advanced predictive models and personalized recommendation systems? If you have hands‐on experience, and a desire to make a significant … graph databases and knowledge graphs, to generate deep insights into financial markets and enhance Marquee’s platform engagement. We collaborate closely with Sales, Trading, Engineering, Product, Design, other areas of the Global Markets Division, and directly with clients. Our global team comprises experts in financial markets, product structuring, cutting ...

Principal, AI/ML Engineer leads the design, delivery and continuous improvement of AI and ML solutions within their area of responsibility, aligning engineering activities to the Bank’s broader AI strategy and long-term objectives. The role combines strong technical leadership with a clear focus on delivery outcomes … operates with a clear understanding of the wider technology landscape, contributing to strategic direction while taking accountability for translating this into practical, high-quality engineering outcomes across squads. Leads the definition and execution of AI/ML engineering direction across one or more squads, ensuring alignment with ...

Lead, Applied Scientist and Research Engineer positions—for upcoming roles across applied machine learning, generative AI, MLOps and model productionisation. These are hands-on engineering roles where you'll build, train, ship and operate the models that drive real product behaviour and real business outcomes. You'll work across … lifecycle—from problem framing and data preparation through to model development, evaluation, deployment, monitoring and iteration. The role suits someone who pairs solid software engineering foundations with genuine ML rigour and a healthy scepticism about what models can and can't be trusted to do. Key Responsibilities Partner with ...

graph databases and knowledge graphs, to generate deep insights into financial markets and enhance Marquee’s platform engagement. We collaborate closely with Sales, Trading, Engineering, Product, Design, and other areas of the Global Markets Division, and directly with clients. Our global team comprises experts in financial markets, product structuring …/PyTorch), Jupyter, Trino, SQL, and gain exposure to graph database technologies. RESPONSIBILITIES AND QUALIFICATIONS Responsibilities: Design, build, and maintain robust data pipelines for feature engineering and model training, ensuring data quality, scalability, and explainability. Develop, train, and deploy state‐of‐the‐art machine learning models, with ...

Python and SQL skills Experience developing and deploying machine learning models into production environments Excellent understanding of statistical modelling, experimentation, and model evaluation Strong feature engineering and exploratory data analysis capabilities Experience communicating technical findings and insights to non-technical stakeholders A degree qualification (BSc, MSc, PhD etc. … innovation The Senior Data Scientist role will involve: Developing and deploying machine learning models to solve real-world business challenges Performing exploratory data analysis, feature engineering, model development, and evaluation Building forecasting, classification, segmentation, and predictive modelling solutions Designing and executing statistical analyses and experiments to support strategic ...

taxonomies, citations, metadata, and content from every scientific discipline. Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI. Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization … inference, experimentation, monitoring, and continuous improvement. Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data science systems. Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical ...

generating, deploying and continuously improving bespoke machine learning models for every customer. You'll work with large-scale behavioural event data, applying machine learning, feature engineering and experimentation to improve prediction accuracy and drive measurable customer outcomes. Working alongside highly experienced founders and recognised experts in machine learning … business. Skills & Experience Strong commercial experience building machine learning models in Python Excellent understanding of predictive modelling, classification or propensity modelling Experience with feature engineering, model evaluation and experimentation Comfortable working across the full machine learning lifecycle Experience working with cloud platforms and modern ML tooling Curious ...

technical leadership across the full lifecycle of machine learning systems powering a new matching platform. This role is accountable for defining ML architecture, establishing engineering standards, driving MLOps maturity, and ensuring that our models are scalable, secure, explainable, and governed to enterprise‐grade standards. You will contribute … compliance framework. This is a highly hands‐on, highly technical, principal‐level role that combines architectural vision with deep practical expertise in ML engineering and AWS-native MLOps. Key Responsibilities Technical Leadership & Architecture Define the end‐to‐end ML architecture for the matching platform, including data pipelines, model training ...

possible with our data and handing those proofs to engineering.\ NAbout the Role:\ NAs a Data Scientist at Third Bridge, you will be the engineering-focused prototyping engine within a high-impact data team. Working alongside our senior analytics capability and reporting to the Principal Data Architect, your primary … proof-of-concept (PoC) solutions — from new dataset pipelines and ML models to AI-powered internal tools — and hand off successful proofs to the engineering team for production integration.\ NYou will work with Third Bridge’s rich proprietary data assets: transcripts, events, interaction data, commercial performance metrics, and content ...

possible with our data and handing those proofs to engineering.\ NAbout the Role:\ NAs a Data Scientist at Third Bridge, you will be the engineering-focused prototyping engine within a high-impact data team. Working alongside our senior analytics capability and reporting to the Principal Data Architect, your primary … proof-of-concept (PoC) solutions — from new dataset pipelines and ML models to AI-powered internal tools — and hand off successful proofs to the engineering team for production integration.\ NYou will work with Third Bridge’s rich proprietary data assets: transcripts, events, interaction data, commercial performance metrics, and content ...

data and handing those proofs to engineering. \n About the Role: \n As a Data Scientist at Third Bridge, you will be the engineering-focused prototyping engine within a high-impact data team. Working alongside our senior analytics capability and reporting to the Principal Data Architect, your primary mandate … proof-of-concept (PoC) solutions — from new dataset pipelines and ML models to AI-powered internal tools — and hand off successful proofs to the engineering team for production integration. \n You will work with Third Bridge’s rich proprietary data assets: transcripts, events, interaction data, commercial performance metrics ...

data and handing those proofs to engineering. \n About the Role: \n As a Data Scientist at Third Bridge, you will be the engineering-focused prototyping engine within a high-impact data team. Working alongside our senior analytics capability and reporting to the Principal Data Architect, your primary mandate … proof-of-concept (PoC) solutions — from new dataset pipelines and ML models to AI-powered internal tools — and hand off successful proofs to the engineering team for production integration. \n You will work with Third Bridge’s rich proprietary data assets: transcripts, events, interaction data, commercial performance metrics ...

connect them with exceptional professionals for this role.\ NJOB DESCRIPTION\ NAs a Software Engineer II - Applied AI in the AI/ML for Engineering team at JPMorganChase, you'll be at the forefront of AI innovation, combining cutting-edge techniques with unique data assets to optimise business decisions … automate processes. This role offers a unique blend of artificial intelligence and software engineering, allowing you to advance engineering processes and build impactful products.In this role, you will leverage the latest research in Large Language Models, Natural Language Processing and statistical machine learning to build AI-powered products ...

them with exceptional professionals for this role. \n JOB DESCRIPTION \n As a Software Engineer II - Applied AI in the AI/ML for Engineering team at JPMorganChase, you'll be at the forefront of AI innovation, combining cutting-edge techniques with unique data assets to optimise business decisions … automate processes. This role offers a unique blend of artificial intelligence and software engineering, allowing you to advance engineering processes and build impactful products. In this role, you will leverage the latest research in Large Language Models, Natural Language Processing and statistical machine learning to build AI-powered ...

NDesign and implementrobust evaluation frameworks to systematically assess and measure the performance of AI agents across key operational metrics.\ NPractice advanced prompt and context engineering (e.G., Chain-of-Thought, ReAct, function calling/tool-use prompts), implement output validation and guardrails to reduce hallucinations.\ NDeploy scalable AI services … .\ N\n\nExperience with generative models (transformers, GANs/VAEs; diffusion models a plus).\ N\n\nStrong understanding of data preprocessing, feature engineering, and evaluation techniques.\ N\n\nFamiliarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).\ N\n\nStrong communication skills ...

what we offer.\ NJob Description\ NAbout the role:\ NJoin us as a SoftwareEngineer in our critical Scam Prevention team. This is a high-impact engineering role with a strong product focus, dedicated to solving complex, real-world adversarial problems to directly protect our global customer base.\ NHow we work … complex technical concepts across teams (Product, Data Science, Investigations).\ N\n\nNiceto Have:\ N\n\nFamiliarity with the machine learning lifecycle (data pipelines, feature engineering, and deploying ML systems into production).\ N\n\nInterested? Find out more:\ N\n\nHow we work – a practical guide ...

offer.\ NJob Description\ NAbout the role:\ NJoin us as a Senior Software Engineer in our critical Account Integrity team. This is a high-impact engineering role with a strong product focus, dedicated to solving complex, real-world adversarial problems to directly protect our global customer base.\ NHow we work … complex technical concepts across teams (Product, Data Science, Investigations).\ N\n\nNiceto Have:\ N\n\nFamiliarity with the machine learning lifecycle (data pipelines, feature engineering, and deploying ML systems into production).\ N\n\nInterested? Find out more:\ N\n\nHow we work – a practical guide ...

agent tools and APIs to connect agents with external services, databases, and internal systems, ensuring robust output parsing and error handling.\ NPractice advanced prompt engineering and implement output validation and guardrails to reduce hallucinations.\ NDesign microservices-based architectures and orchestrate multi-step workflows; instrument agents for tracing, metrics … with agent frameworks such as LangChain, CrewAI, AutoGen, LangGraph.\ NKnowledge of generative models including transformers, GANs, VAEs, and diffusion models.\ NUnderstanding of data preprocessing, feature engineering, and model/agent evaluation techniques.\ NFamiliarity with cloud platforms and containerization technologies.\ NStrong problem-solving skills and ability to work independently ...

tools and APIs to connect agents with external services, databases, and internal systems, ensuring robust output parsing and error handling. \n Practice advanced prompt engineering and implement output validation and guardrails to reduce hallucinations. \n Design microservices-based architectures and orchestrate multi-step workflows; instrument agents for tracing, metrics … frameworks such as LangChain, CrewAI, AutoGen, LangGraph. \n Knowledge of generative models including transformers, GANs, VAEs, and diffusion models. \n Understanding of data preprocessing, feature engineering, and model/agent evaluation techniques. \n Familiarity with cloud platforms and containerization technologies. \n Strong problem-solving skills and ability ...

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

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

understanding of JDBC and database internals.\ NExperience with CI/CD pipelines and Distributed and Concurrent Systems\ NExperience with machine learning basics (data pipelines, feature engineering, recall/precision, familiarity with machine learning systems in production) is a huge plus\ NA strong product mindset and passion for user … nHow we work – a practical guide\ NDEI @ Wise\nWise Tech Stack (2025 update)\ NSee what it's like to work at Wise London!\ NOur Engineering career map\ N\nWise Engineering – https://medium.Com/wise-engineering\ NWhat do we offer: \ N\nStarting salary ...

Join our global Quantitative Trading & Research (QTR) team, where you’ll apply your expertise in Derivatives Modelling, Financial Engineering, Data Science, and Quantitative Development. As part of JP Morgan’s leading QTR Group, you’ll innovate with unique analytics and mathematical models, enhancing business practices through automation. We develop … limitations, and model performance. Build and productionize analytics that advance intraday/EoD automation (services, APIs, pipelines) with clear SLOs/SLA, observability, reliability engineering practices, and tight integration into trading/risk platforms. Provide technical leadership and mentorship; conduct code/method reviews, establish research engineering best ...