17 of 17 Contract MLOps Jobs in London

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/inference workflows Ability to translate business problems into analytical tasks ...

with Microsoft Fabric, OneLake architecture and Azure AI Foundry Experience designing AI governance frameworks, model risk management and Responsible AI controls Background in delivering MLOps, intelligent document processing (IDP) or LLM-based solutions at enterprise scale ...

Searches: ML Engineer/AI Engineer/Cloud Engineer/Machine Learning/Cloud AI/Google Cloud/GCP/Vertex AI/MLOps/ML Ops/AIOPs/AI Ops/ ...

stakeholders to prioritise backlogs, manage risks, and translate requirements into actionable technical plans. Establish and enforce engineering best practices -including coding standards, DevOps/MLOps pipelines, testing frameworks, and documentation-to ensure high-quality delivery. Drive innovation by evaluating emerging data and AI technologies, leading proofs of concept, and embedding ...

traditional ML solutions end-to-end Comfortable in startup or scale-up environments — fast-moving, iterative, delivery-focused Strong Python engineering experience Experience with MLOps, CI/CD, IaC, and productionising ML models Ability to work collaboratively with product, data, and engineering teams Contract Details Location: Hybrid London ...

inference performance via batching, quantisation, distillation, LoRA/PEFT, accelerator utilisation (GPU/TPU), and efficient memory/latency tuning Build and maintain MLOps/LLMOps workflows-CI/CD for models and prompts, model registry/versioning, feature stores, and automated promotion across environments Instrument observability for data, models … Gateways and ISTIO, ability to Diagnose and intercept failures in End to End communication Implement best practices for data governance, security, and MLOps on GCP Proficiency with Python and common AI/ML frameworks such as TensorFlow, PyTorch, JAX, scikit learn, and Hugging Face libraries Knowledge of MLOps and LLMOps ...

ongoing BAU support and maintenance of data structures, schema, reporting etc. Work with the broader Engineering community to develop the client's data and MLOps capability infrastructure Ensure data quality, governance, and compliance with internal and external standards. Monitor and troubleshoot data pipeline issues, ensuring reliability and accuracy. ...

development Solid understanding of anomaly detection techniques Experience building data workflows/pipelines Desirable: Experience working in secure/government environments Knowledge of MLOps best practices Familiarity with real-time or near real-time data processing Contract Details: Location: London (hybrid) Duration: 6 months Day Rate: Up to £595/ ...

practices across their ML and data setup, ensuring it is ready to support multiple enterprise deployments. Key responsibilities: * Audit current ML architecture, pipelines, and MLOps practices * Identify gaps in documentation, reproducibility, and scalability * Introduce clear structure across model development, versioning, and deployment * Improve training and retraining workflows * Strengthen model monitoring … Python and hands-on ML engineering experience * Proven experience in productionising ML systems end-to-end * Experience auditing and improving existing ML setups * Strong MLOps experience (model versioning, monitoring, CI/CD) * Experience working with data pipelines (ETL/ELT, Spark or similar) * Comfortable working with messy, real-world data ...

clear service boundaries Define enterprise-wide AI architecture guidelines, reusable components, and long-term roadmap to ensure consistency and acceleration of AI initiatives Implement MLOps/LLMOps pipelines for versioning, CI/CD, approvals, and controlled promotion across environments; enforce reproducibility Work closely with product owners, data scientists, engineers, security … Deep understanding of LLMs, generative AI, RAG patterns, vector databases, embeddings, and prompt/guardrail engineering Desirable Skills/Knowledge/Experience Knowledge of MLOps/AgentOps, CI/CD, and observability Strong understanding of regulated financial services environments Proven experience implementing AI risk controls, model governance, and auditability Ensure ...

clear service boundaries. Define enterprise-wide AI architecture guidelines, reusable components, and long-term roadmap to ensure consistency and acceleration of AI initiatives. Implement MLOps/LLMOps pipelines for versioning, CI/CD, approvals, and controlled promotion across environments; enforce reproducibility. Work closely with product owners, data scientists, engineers, security … Deep understanding of LLMs, generative AI, RAG patterns, vector databases, embeddings, and prompt/guardrail engineering. Desirable skills/knowledge/experience: Knowledge of MLOps/AgentOps, CI/CD, and observability. Strong understanding of regulated financial services environments. Proven experience implementing AI risk controls, model governance, and auditability. Ensure ...

transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low-latency, highly reliable cloud … strong hands-on use of ML/DL frameworks (e.g., PyTorch, TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure-as-code practices. Proven technical leadership experience including ...

This is a fantastic opportunity to work as an MLOps Engineer on a remote basis, outside IR35, for a major pharmaceutical company. The key skills required for this MLOps Engineer position are: MLOps Image data Terraform AWS PyTorch, TensorFlow, JAX If you do have the relevant experience for this long … term remote contract MLOps Engineer role, outside IR35, please do apply. ...

This is a fantastic opportunity to work as an MLOps Engineer on a remote basis, outside IR35, for a major pharmaceutical company. The key skills required for this MLOps Engineer position are: MLOps Image data Terraform AWS PyTorch, TensorFlow, JAX If you do have the relevant experience for this long … term remote contract MLOps Engineer role, outside IR35, please do apply click apply for full job details ...

I am recruiting for a Data Scientist to work on a hybrid basis - 2-3 days in London, remaining time remote. The role falls inside IR35 so you will be required to work through an ...

deliver cloud and on-prem infrastructure solutions aligned to security and governance standards Lead architecture across AI/ML workloads , including LLMs and MLOps environments Work closely with security, networking and data teams to ensure resilient, compliant solutions Own high- and low-level designs (HLD/LLD) and support project … complex environments (NHS or regulated sectors beneficial) Strong Azure and/or AWS infrastructure architecture Experience supporting AI/ML platforms , including LLMs and MLOps Knowledge of GPU virtualisation/high-performance compute environments Solid understanding of networking, firewalls, identity (Entra ID/AD) and security best practice Experience across ...

ingestion pipelines to the deployment of advanced GenAI models. This is a hands-on leadership role requiring a deep understanding of modern data architecture, MLOps, and the orchestration of agentic workflows. Key Responsibilities Lead Delivery: Oversee the end-to-end lifecycle of data-intensive platforms and AI solutions aligned with … architecture. Technical Direction: Provide guidance across cloud engineering, data modeling, and ML model monitoring. Engineering Excellence: Enforce best practices in coding standards, DevOps/MLOps pipelines, and automated SDLC. Stakeholder Management: Translate complex business requirements into actionable technical backlogs for engineering teams. Innovation: Evaluate emerging GenAI/LLM tech ...