19 of 19 Remote/Hybrid Feature Engineering Jobs in London

solution offerings. Provide expertise and guidance on AI best practices, contributing to the organization's AI strategy and innovation efforts. Conduct data analysis and feature engineering to prepare data for use in AI models, utilizing Azure Data Lake and other data storage solutions. Develop robust testing and validation … Cognitive Services, Azure Functions, and container services. Familiarity with Azure data services is a plus. Solid background in machine learning algorithms, data pre-processing, feature engineering, and model evaluation is a big plus. Experience with deep learning frameworks like TensorFlow or PyTorch is desirable. Proficiency in handling large ...

solution offerings. Provide expertise and guidance on AI best practices, contributing to the organization's AI strategy and innovation efforts. Conduct data analysis and feature engineering to prepare data for use in AI models, utilizing Azure Data Lake and other data storage solutions. Develop robust testing and validation … Cognitive Services, Azure Functions, and container services. Familiarity with Azure data services is a plus. Solid background in machine learning algorithms, data pre-processing, feature engineering, and model evaluation is a big plus. Experience with deep learning frameworks like TensorFlow or PyTorch is desirable. Proficiency in handling large ...

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 ...

Designing, developing, and deploying LLM applications (e.g. GPT, LLaMA, Claude) integrated with RAG pipelines Implementing end-to-end workflows: from data acquisition, cleaning, and feature engineering to model training, deployment, and monitoring Building scalable pipelines and APIs for AI services in cloud environments (AWS, Azure, or GCP) Collaborating … learning What We’re Looking For: A recently completed Master’s degree from a Russell Group university in Artificial Intelligence, Computer Science, Data Science, Engineering, Mathematics, or a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills ...

Designing, developing, and deploying LLM applications (e.g. GPT, LLaMA, Claude) integrated with RAG pipelines Implementing end-to-end workflows: from data acquisition, cleaning, and feature engineering to model training, deployment, and monitoring Building scalable pipelines and APIs for AI services in cloud environments (AWS, Azure, or GCP) Collaborating … learning What We’re Looking For: A recently completed Master’s degree from a Russell Group university in Artificial Intelligence, Computer Science, Data Science, Engineering, Mathematics, or a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills ...

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. ...

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 ...

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 ...

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 ...

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 ...

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 ...

heart of its strategy, investing heavily in both classic ML and next-generation AI capabilities. This is a company that blends modern product engineering with a fast-moving, high-ownership culture. Their environment encourages experimentation, cross-functional collaboration, and the freedom to shape what “great” looks like in machine … infrastructure. This is a hybrid hands-on/leadership role, ideal for someone who thrives at the intersection of applied research, platform integration, and engineering-minded data science. What You’ll Be Doing Build and deploy a wide variety of models spanning classification, regression, propensity scoring, and LLM-based ...

heart of its strategy, investing heavily in both classic ML and next-generation AI capabilities. This is a company that blends modern product engineering with a fast-moving, high-ownership culture. Their environment encourages experimentation, cross-functional collaboration, and the freedom to shape what “great” looks like in machine … infrastructure. This is a hybrid hands-on/leadership role, ideal for someone who thrives at the intersection of applied research, platform integration, and engineering-minded data science. What You’ll Be Doing Build and deploy a wide variety of models spanning classification, regression, propensity scoring, and LLM-based ...

translate insights into business impact. Key Responsibilities Design and implement predictive and prescriptive models for MRO AI Solutions. Perform exploratory data analysis and feature engineering. Collaborate with Data Engineers to ensure data readiness for modeling. Communicate findings and recommendations to business stakeholders. Continuously improve models based on feedback ...

translate insights into business impact. Key Responsibilities Design and implement predictive and prescriptive models for MRO AI Solutions. Perform exploratory data analysis and feature engineering. Collaborate with Data Engineers to ensure data readiness for modeling. Communicate findings and recommendations to business stakeholders. Continuously improve models based on feedback ...

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 ...

Flexible daily rate (inside IR35) Key Responsibilities Design and implement predictive and prescriptive models for MRO AI Solutions. Perform exploration data analysis and feature engineering. Collaborate with Data Engineers to ensure data readiness for modeling. Communicate findings and recommendations to business stakeholders. Continuously improving models based on feedback ...

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 ...

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 ...