8 of 8 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 ...

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 ...

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 ...

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 ...

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 ...