26 to 50 of 88 Feature Engineering Jobs in England

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 ...

responsibilities and tasks associated with this role before proceeding. JOB DESCRIPTION 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 ...

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 ...

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 ...

retries.Design and implement robust evaluation frameworks to systematically assess and measure the performance of AI agents across key operational metrics.Practice advanced prompt and context engineering (e.g., Chain-of-Thought, ReAct, function calling/tool-use prompts), implement output validation and guardrails to reduce hallucinations.Deploy scalable AI services to cloud … LangChain, CrewAI, AutoGen, LangGraph, ADK). Experience with generative models (transformers, GANs/VAEs; diffusion models a plus). Strong understanding of data preprocessing, feature engineering, and evaluation techniques. Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). Strong communication skills for both technical ...

implement robust evaluation frameworks to systematically assess and measure the performance of AI agents across key operational metrics. Practice advanced prompt and context engineering (e.g., Chain-of-Thought, ReAct, function calling/tool-use prompts), implement output validation and guardrails to reduce hallucinations. Deploy scalable AI services to cloud … LangChain, CrewAI, AutoGen, LangGraph, ADK). Experience with generative models (transformers, GANs/VAEs; diffusion models a plus). Strong understanding of data preprocessing, feature engineering, and evaluation techniques. Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). Strong communication skills for both technical ...

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 ...

security platform, contributing to innovative features that leverage advanced analytics, behavioural detection, and intelligent threat prevention. Working as part of a highly collaborative engineering team, you will help bridge the gap between cutting-edge machine learning research and production-grade security software. To see what our engineering teams … design and implementation of intelligent threat detection, behavioural analysis, and anomaly detection capabilities. Participate in architecture discussions, code reviews, testing, and continuous improvement of engineering practices. Evaluate emerging AI technologies and contribute to future product innovation. Requirements for the C++ AI/ML Software Engineer Strong proficiency in modern ...

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 ...

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

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

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 ...

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 ...

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

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

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 ...

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 ...

offer. Job Description About the role: Join 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. How we work … securing customers' money, accelerating product growth by raising automation levels, and helping us engineer a world-class money transfer product. What do you need? Engineering Expertise: Professional experience with Java or other JVM-based languages, including the Spring framework. Experience building and designing scalable web applications that handle large ...

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 ...

queries and manage remediation actions and findings Your skills and experience Advanced degree (Master’s or PhD) in a quantitative discipline (e.g., Mathematics, Physics, Engineering, Computer Science) 7+ years’ experience developing analytical or machine learning models in financial services (ideally Anti-Financial Crime/Screening) Experience building Natural Language … Processing (NLP)/Machine Learning (ML)/Artificial Intelligence (AI) pipelines, including feature engineering, model training, evaluation and monitoring Experience designing evaluation frameworks for LLM use cases (e.g., human-in-the-loop, calibration, guardrails, auditability) Experience with hyperparameter tuning at scale and experimentation frameworks Strong technical experience with ...

logistic regression, gradient boosting, random forests, clustering, NLP Proficient in Python and/or R, with strong experience in data quality, model development and feature engineering Strong command of SQL and familiarity with data engineering environments such as Databricks or similar Skilled in data visualisation and storytelling ...