9 of 9 Remote/Hybrid 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 ...

real-world value from data by architecting models, pipelines, and integration patterns that scale across the organisation. This role combines technical depth, applied ML engineering, solution design, and hands-on development. Key Responsibilities Design, build, and train end-to-end machine learning models across NLP, predictive analytics, classification … cases Experiment with algorithms, optimise hyperparameters, and evaluate model performance Collect, process, and prepare structured and unstructured datasets for model training and validation Implement feature engineering, data augmentation, and data quality controls Develop APIs, services, or microservices to integrate models into production platforms Deploy, monitor, and manage 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. ...

other AI applications. Experiment with algorithms and optimize hyperparameters for performance. Data Preparation Collect, clean, and preprocess large datasets for training and validation. Implement feature engineering and data augmentation techniques. Integration & Deployment Develop APIs or services to integrate ML models into production systems. Work with MLOps tools … practices. Implement bias detection and mitigation strategies. Your Profile Essential Skills/Knowledge/Experience (Up to 10) 10+ years of experience in software engineering, with 5+ years in AI/ML. Expert in Python, PyTorch, TensorFlow, and NLP frameworks. Proven experience with LLMs, transformer architectures, and LangChain/ ...

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 ...

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 ...

ensemble methods etc Experience with MLOps including model deployment, CI/CD and unit testing. (GIT, Azure devops etc) Experience in building ML pipelines, feature engineering and ability to handle large dataset for business insights. Experience with model governance including explainability, observability and documentations Scala and Python knowledge ...

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 ...