9 of 9 Contract Machine Learning Jobs in Central London

making. Collaborate with data engineers, analysts, product managers, and domain experts to translate business requirements into well-defined modelling tasks. Build end to end ML pipelinesfrom feature engineering and preprocessing to deployment ready model outputs. Apply advanced techniques such as NLP, time series forecasting, anomaly detection, optimisation, or LLM/… exploratory data analysis. Familiarity with LLMs, NLP techniques, and GenAI frameworks, including embeddings, prompt engineering, or fine tuning. Experience building end to end ML pipelines, including model validation, optimisation, deployment, and monitoring. Understanding of MLOps practices, including model versioning, model registries, CI/CD for ML, and automated training/ ...

strengthening operational resilience, and helping organisations realise the full potential of an AI enabled future. Your responsibilities: Build and ship production ready AI/ML featuresfrom data ingestion and feature engineering to model training, evaluation, and deployment. Develop LLM/GenAI solutions (prompt engineering, tool use, guardrails) and RAG pipelines … reviews, write unit/integration/e2e tests (including data and prompt tests), and uphold engineering standards and documentation. Work with advanced AI/ML frameworks, cloud services, and container orchestration platforms. As an AI Engineer, you are responsible for designing, building, and deploying scalable AI and machine learning ...

across real assets, sustainability, and essential services . What you'll do Build and enhance our cloud platforms and data infrastructure Deploy AI/ML and GenAI solutions into production Drive automation and operational efficiency using AI and RPA Support development of client-facing digital platforms and dashboards Modernise systems ...

Proven track record building data science platforms or research environments * Strong grounding in data engineering principles (pipelines, governance, data access) * Experience integrating AI/ML services, including Amazon Bedrock * Ability to design and expose APIs/services for data and notebook interoperability * Experience working in enterprise or regulated environments Nice ...

fast moving, data rich industries to operate, scale, and innovate. You will develop robust, production ready AI solutions that harness automation, advanced analytics, and machine learning click apply for full job details ...

with engineering, security, and support teams to enable deployment, monitoring, and scaled adoption of AI products. Foster a culture of innovation, encouraging experimentation, continuous learning, and collaborative problem-solving across multidisciplinary teams. Your Profile AI Senior Product Owner (9+ Years) Essential skills/knowledge/experience: Proven senior level … vendors and strategic AI platform partners Clear, confident communicator able to operate at delivery, senior leadership, and executive level Strong understanding of AI/ML concepts, including model lifecycle, data pipelines, experimentation, model evaluation, and responsible AI principles. Experience working with modern AI technologies such as LLMs, generative AI, predictive ...

observability using Cloud Logging, Cloud Monitoring, Error Reporting, Trace, and Profiler; build model/LLM telemetry dashboards and alerts. Identify the right AI/ML frameworks, cloud services, model orchestration tools, and infrastructure components that align with business needs and scalability goals Architect APIs, microservices, and integration patterns that embed … model risk management, and LBG internal policies. Knowledge of banking processes: retail banking, lending, payments, compliance. Strong experience designing end to end AI/ML architectures, including data ingestion, feature engineering, model training, deployment, and monitoring. Hands on expertise with cloud AI platforms (GCP). Strong knowledge of LLMOps practices ...

schema validation, completeness, freshness, thresholds, and automated alerting. Enhance end-to-end pipeline resilience, monitoring, observability, failure handling, and recovery mechanisms. Integrate AI/ML features to boost reliability, anomaly detection, and operational efficiency. Collaborate closely with Data Product teams, Analytics Engineering, and Data Science to deliver production-grade data … expectations. Preferred Experience: Exposure to AI-enabled pipeline capabilities, such as anomaly detection or intelligent monitoring. Good understanding of MLOps or supporting deployment of ML models into production environments. Experience with CI/CD automation, testing frameworks, and observability tooling. Contracting Route: Timesheets via Umbrella Company This is an exceptional ...

data enabled future. Your responsibilities: Define and maintain conceptual, logical, and physical data models that accurately reflect business processes and support analytics, AI/ML, and operational needs. Translate business requirements into robust data entities, attributes, relationships, and constraints; ensure traceability from requirements to models. Establish and enforce GDM modelling … . Drive data integration design across sources (CDC, event streaming, APIs), mapping source-to-target, resolving conflicts, and handling historical changes. Support AI/ML readiness by modelling features, aggregations, and histories; collaborate on feature stores and model input/output schemas. Embed privacy and security requirements into models ...