25 of 25 Feature Engineering Jobs in London

integrate LLM-powered solutions for tracing, evaluation, and production monitoring. Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails. Design feature engineering approaches and contribute to feature store development. Support production models through monitoring, performance analysis, and continuous improvement. Apply responsible AI practices … governance and quality controls. Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, DVC). Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures. Familiarity with LLMOps tooling (LangSmith, LangChain, LangGraph). Understanding of model evaluation, validation, and production monitoring. Strong problem-solving skills ...

Engineer to design, build and operationalise advanced machine learning solutions that directly support UK national security objectives. This role sits within a multidisciplinary AI engineering environment, working closely with Data Scientists, Software Engineers, Product teams and government stakeholders. The Senior ML Engineer will own the journey from experimentation … including hypothesis definition, experimental design, evaluation and iteration, while complying with governance standards Transitioning validated experiments into production-ready ML services, collaborating closely with engineering teams on deployment and monitoring Building scalable ML pipelines using AWS services and modern experiment tracking frameworks Developing and integrating LLM-powered capabilities ...

integrate LLM-powered solutions for tracing, evaluation, and production monitoring Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Design feature engineering approaches and contribute to feature store development Support production models through monitoring, performance analysis, and continuous improvement Apply responsible AI practices … quality controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures It Would Be Great If You Also Had Experience In Some Of These, But If Not Well Help You With Them Experience ...

integrate LLM-powered solutions for tracing, evaluation, and production monitoring Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Design feature engineering approaches and contribute to feature store development Support production models through monitoring, performance analysis, and continuous improvement Apply responsible AI practices … Them Experience with advanced LLM techniques: agents, tool use, and agentic workflows Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications Experience with feature stores (Feast, AWS Feature Store) Experience with containerisation (Docker) and orchestration (Kubernetes ...

Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering, and MLOps practices for production deployment. Generative AI & LLM Integration - Proficient in working with Large Language Models including OpenAI GPT models, Anthropic … Claude, Azure OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding. Appian BPA Platform - Strong experience with Appian low-code platform including ...

Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering, and MLOps practices for production deployment. Generative AI & LLM Integration - Proficient in working with Large Language Models including OpenAI GPT models, Anthropic … Claude, Azure OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding. Appian BPA Platform - Strong experience with Appian low-code platform including ...

critical role in designing, building, and maintaining data pipelines and infrastructure that enable the development and deployment of machine learning models and drive engineering excellence. You will collaborate closely with data scientists, and lead ML engineers, and software engineers to ensure data is clean, accessible, and optimised for large … systems (e.g., PySpark, Hadoop). Data Preparation: Collaborate with data scientists to prepare and transform raw data into formats suitable for machine learning, including feature engineering and data augmentation. Automation: Implement automation tools and frameworks (CI/CD) to streamline the deployment and monitoring of machine learning models ...

with data engineers and AI engineers on interfaces and SLAs. Required Skills & Experience Python (pandas, NumPy, scikit-learn; PyTorch/TF a plus). Feature engineering, data quality validation, model training and optimisation. MLOps: experiment tracking (e.g., MLflow), model registry, CI/CD for ML. Serving and orchestration … monitoring for drift/perf. Nice to Have Cost/performance optimisation on AWS; GPU scheduling; quantisation/distillation. Experience working within Financial Services engineering standards and governance. IND_PC3 Guidant, Carbon60, Lorien & SRG - The Impellam Group Portfolio are acting as an Employment Business in relation to this vacancy. ...

Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor's or Master's in Data Science ...

discovery and design of AI strategies, governance models and platform architectures aligned to business outcomes. • Design end-to-end AI solutions, including data ingestion, feature engineering, ML/GenAI models, MLOps and deployment. • Support pre-sales activity, including solution shaping, technical validation, demos and customer presentations. • Bridge multiple … Azure or GCP). • Exposure to private/on-prem AI platforms (e.g. NVIDIA-based stacks, private AI platforms). • Solid understanding of data engineering concepts (ETL, data lakes, Spark or similar). • Experience designing scalable, distributed systems. • Familiarity with model lifecycle management and MLOps practices. • Proven ability ...

frameworks (TensorFlow, PyTorch, Scikit-learn). •Hands-on experience with MLOps, CI/CD pipelines, and model monitoring. •Knowledge of cloud architecture, data engineering, and security best practices. •Design and implement ML pipelines on Azure Machine Learning. •Own end-to-end model lifecycle: data ingestion, feature engineering ...

services (SageMaker, Lambda) Familiarity with containerisation (Docker) and orchestration (Kubernetes/ECS) Knowledge of LLMOps and GenAI tools (LangChain, LangSmith) Understanding of feature engineering and vector databases Strong grasp of CI/CD practices for ML deployment Why Join Us: Work with niche datasets and cutting-edge tech ...

employees' passion for travel and ensure a rewarding career journey. We’re building a more open world. Join us. Expedia Group’s Advertising Engineering team is dedicated to building innovative solutions that empower travel advertisers to connect with millions of travelers worldwide. Our platform enables brands to leverage Expedia … solutions for the advertising domain. In this role, you will: Design, implement, and maintain large-scale machine learning pipelines for advertising use cases, including feature engineering, model training, validation, and deployment. Build real-time and batch data processing systems to support ad targeting, campaign optimisation, and experimentation. Collaborate ...

Senior Data Scientist to take a leading role across a portfolio of technically demanding projects. You’ll operate end-to-end - shaping problem definitions, engineering data pipelines, developing advanced models, and ensuring outputs are robust, explainable and deployable in real-world settings. This is a hands-on role … impact. Key Responsibilities Translating complex, ambiguous problem statements into clear, actionable data science solutions. Owning the full data science lifecycle, from data ingestion and feature engineering through to modelling, evaluation and deployment. Developing statistical, machine learning and deep learning models to support high-impact, real-world decision making. ...

Collaborate with data engineers, analysts, and product teams to translate business needs into AI-driven solutions Contribute to the development of data pipelines and feature engineering workflows Integrate models into production using APIs, batch jobs, or real-time systems Apply best practices around experimentation, evaluation, versioning, and monitoring ...

services. Solid knowledge and experience of AI and ML is essential Key responsibilities include; Python (pandas, NumPy, scikit-learn): For data wrangling, modelling, and feature engineering SQL: For querying structured data sources Model Development & Validation: Experience with classification, unsupervised learning (e.g. outlier detection), and ranking models Machine Learning ...

value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/… with cross-functional teams, including engineers, product leads, and client stakeholders Bachelor’s or Master’s degree in a quantitative field (e.g., Mathematics, Physics, Engineering, Computer Science) from a strong university Excellent communication skills and a collaborative mindset Please note: This role cannot offer VISA sponsorship ...

linked data science solutions. Working closely with data engineers to define data requirements and pipelines. Performing exploratory data analysis and recreating key business KPIs. Feature engineering in collaboration with machine learning engineers, ensuring production-ready standards. Developing, deploying and maintaining machine learning models. Evaluating project impact through experimentation ...

linked data science solutions. Working closely with data engineers to define data requirements and pipelines. Performing exploratory data analysis and recreating key business KPIs. Feature engineering in collaboration with machine learning engineers, ensuring production-ready standards. Developing, deploying and maintaining machine learning models. Evaluating project impact through experimentation ...

value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Act as a technical lead … with cross-functional teams, including engineers, product leads, and client stakeholders Bachelor’s or Master’s degree in a quantitative field (e.g., Mathematics, Physics, Engineering, Computer Science) from a strong university Excellent communication skills and a collaborative mindset Please note: This role cannot offer VISA sponsorship ...

extensive work experience in the related field. Good understanding of cardiovascular diseases, risk factors and clinical workflows. Expertise in handling missing data, outliers and feature engineering. Experience in processing Health data from various sources (EHR, Wearables) and formats (e.g., HL7/FHIR, CSV, PDF, PNG, JPEG). Skilled ...

Cleaning, structuring, and ingesting behavioral tracking data for ML models. Other key responsibilities: Collaborating with a lead data scientist and marketing expert to refine feature engineering and ensure data quality. SKILLS AND EXPERIENCE The successful Data Engineer will have the following skills and experience: 4–6 years … hands-on experience in data engineering , ideally in startups, consumer subscription apps, or MarTech . Strong Python skills (certifications or deep experience with Pandas, Polars ). Experience with behavioral tracking data (e.g., Amplitude, Mixpanel, Segment). Familiarity with dbt, Django, and DevOps/ML workflows . A proactive, founding ...

ground up alongside experienced founders. The role You will: Build production-ready, pythonic data pipelines Create data models to organise raw behavioural data Support feature engineering for machine learning workflows Handle ETL processes and data ingestion across clients Identify and resolve data quality issues Work closely with senior … technical leadership What we're looking for Outstanding Python skills 4+ years in data engineering Experience with data cleansing and ETL pipelines Strong event-level/behavioural data experience Able to work independently and make smart technical decisions Nice to have: pandas/polars dbt Django or backend exposure ...

champion their adoption across teams. Responsibilities •Act as a data strategist to identify, integrate, and leverage new data sources through product capabilities. •Collaborate with engineering teams to build, test, and deploy scalable data products and predictive models. •Execute analytical experiments to address challenges across multiple business domains. •Mine … science or a related field. •Proven expertise in data mining, statistical modelling, and machine learning techniques. •Advanced experience in pattern recognition, predictive modelling, and feature engineering. •Proficiency in Python and SQL, and a solid grasp of software engineering best practices. •Strong understanding of data structures, model evaluation ...

across venues and instruments . Collaborate on real-time risk, monitoring, and control infrastructure. Qualifications 📚 Education Postgraduate degree in Mathematics, Computer Science, Physics, or Engineering from a top university. 📈 Experience & Domain Knowledge 2–5 years of experience owning the full lifecycle of a trading strategy: idea generation → research → modelling … order-book dynamics. Experience in an HFT, proprietary trading, or systematic trading environment . 💻 Technical Skills Strong Python skills for research, modelling, data engineering, and production workflows . Applied ML/DL experience in real-time time-series prediction and feature engineering. Ability to write clean, reliable, performance ...