251 to 275 of 685 MLOps Jobs in England

product portfolio and partner ecosystem. If you are a seasoned engineer who is energised by the challenge of mastering Agentic Systems and building the MLOps pipelines of the future, we want to talk to you. You will be part of a Scrum team to build innovative, standards-compliant, secure ...

delivery at scale. Excellent communication and stakeholder-management skills, with fluent English (written and spoken). Preferred Experience and/or Qualifications Familiarity with MLOps or LLMOps practices, and with monitoring and observing the behaviour of AI systems in production. Exposure to prompt design and prompt/response evaluation techniques ...

Implement bounding guardrails, prompt evaluation, and anti-hallucination controls to ensure 100% compliance with MoD AI ethics, safety, and non-kinetic governance standards. Data & MLOps Pipelines: Build reproducible model training, evaluation, and containerised deployment pipelines capable of operating in air-gapped or low-bandwidth environments. Technical Client Advisory: Translate complex ...

platform builder with an enablement mindset with experience in shipping platform capabilities used by multiple teams.Deep knowledge of cloud-native infrastructure (Kubernetes, networking), MLOps/LLMOps stacks, vector databases/embedding stores, routing/caching layers, and identity/risk management.Strong software engineering skills (e.g., Python/TypeScript/ ...

understanding of the full ML lifecycle and strong software/platform instincts - you know what it takes to run reliable ML at scale – including MLOps tooling and practicesExperience raising operational standards: SLIs/SLOs, monitoring, incident management, and production reliabilityBudget ownership, including infrastructure cost management and vendor oversightComfortable operating ...

ranking, recommendation, or retrieval systemsFamiliarity with scientific, biomedical, or scholarly datasetsExperience with knowledge graphs, ontologies, or semantic enrichment systemsExposure to production ML systems and MLOps practicesAcademic or industry research experience in NLP, information retrieval, search, or generative AIExperience working in content-rich, knowledge-intensive, or highly regulated domainsWorking for youWe ...

scale, vector stores, agentic orchestration, multimodal work, evaluation infrastructure and fine-tuning where it earns its place.You're fluent in the layer underneath: MLOps tooling, deployment and cloud infrastructure (we run on AWS and GCP), and you can tell the difference between a choice that matters and one that doesn ...

scale, vector stores, agentic orchestration, multimodal work, evaluation infrastructure and fine-tuning where it earns its place. You're fluent in the layer underneath: MLOps tooling, deployment and cloud infrastructure (we run on AWS and GCP), and you can tell the difference between a choice that matters and one that ...

obligations. Design scalable, secure, and resilient data platforms, including cloud, hybrid, and on‐premise architectures. Lead architecture for advanced analytics, machine learning, GenAI, and MLOps, ensuring production‐grade robustness. Establish AI governance, data management, and responsible AI frameworks, including security, privacy, explainability, and model risk controls. Translate business outcomes into ...

Reliability role supporting large-scale cloud systems.Experience operating GPU-backed environments or large-scale ML infrastructure.Experience running model training or inference pipelines in production (MLOps).Strong Kubernetes experience, including operating production clusters.Hands-on experience running production workloads in AWS, GCP, or Azure.Experience operating complex distributed systems in production, ideally including ...

applications and AI assistants.Familiarity with scientific, biomedical, or scholarly datasets and workflows.Experience with knowledge graphs, ontologies, or semantic enrichment systems.Exposure to production ML systems, MLOps, and AI governance practices.Publications or applied research contributions in NLP, IR, search, recommendation systems, or generative AI.Experience building AI systems in high-trust, regulated ...

assistants.* Familiarity with scientific, biomedical, or scholarly datasets and workflows.* Experience with knowledge graphs, ontologies, or semantic enrichment systems.* Exposure to production ML systems, MLOps, and AI governance practices.* Publications or applied research contributions in NLP, IR, search, recommendation systems, or generative AI.* Experience building AI systems in high-trust ...

Trips vertical. Talent Multiplier: Mentor and coach senior and mid‐level ML scientists. Foster a culture of technical excellence, driving best practices for MLOps, rigorous A/B testing, data privacy, and code quality. Skills & Experience: Education: Ph.D. or Master’s degree in Computer Science, Machine Learning, Statistics ...

within the Trips vertical.Talent Multiplier: Mentor and coach senior and mid-level ML scientists. Foster a culture of technical excellence, driving best practices for MLOps, rigorous A/B testing, data privacy, and code quality.Skills & Experience:Education: Ph.D. or Master’s degree in Computer Science, Machine Learning, Statistics ...

Trips vertical. Talent Multiplier: Mentor and coach senior and mid-level ML scientists. Foster a culture of technical excellence, driving best practices for MLOps, rigorous A/B testing, data privacy, and code quality. Skills & Experience: Education: Ph.D. or Master’s degree in Computer Science, Machine Learning, Statistics ...

AXA Group is seeking a Lead Data Scientist to drive high-impact data science initiatives across the business. You will lead projects from conception to deployment, build scalable ML models, and mentor a squad of ...

Just Eat Takeaway.com is looking for a Senior Engineer to join their Enterprise AI team in Greater London. The role involves designing and deploying AI-powered solutions, leading projects, and mentoring team members on best ...

operationalization, utilizing cloud-native services (e.g., serverless, containerization, managed AI/ML platforms) and CI/CD pipelines for accelerated delivery. Implement robust MLOps practices to streamline model deployment, monitoring, and lifecycle management in cloud environments, including data versioning, feature store integration, and data pipeline management.Business Partnership & Solution Architecture: Collaborate … existing systems and workflows within the Goldman Sachs ecosystem. Apply strong software engineering principles, data modeling best practices (e.g., relational, NoSQL, graph), DevOps/MLOps best practices, and cloud security standards. Drive automation of deployment, testing, and monitoring processes to ensure rapid and reliable delivery of AI applications.Knowledge Transfer & Enablement ...

Design and implement reusable data products, semantic models and analytics capabilities that support reporting, machine learning and GenAI workloads. Drive adoption of AI Engineering, MLOps and LLMOps best practices across development, deployment, monitoring and governance. Champion security, resilience, privacy, Responsible AI and governance by design. Identify opportunities to improve efficiency … cases. Understanding of modern GenAI architecture patterns including vector databases, retrieval-augmented generation (RAG), embeddings, agentic workflows and LLM orchestration frameworks. Knowledge of MLOps, model lifecycle management, observability and AI governance practices. Experience with cloud platforms such as GCP, Azure or AWS and associated platform services. Strong understanding of containers ...

including machine learning models, data pipelines and application components that are secure, reliable and performant.Drive the operationalisation of AI solutions using modern engineering and MLOps practices, including CI/CD, model monitoring, testing and lifecycle management.Ensure solutions are developed in line with security, privacy, governance and responsible AI requirements, particularly … practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation and evaluation approaches.Experience with MLOps and modern engineering practices, including CI/CD pipelines, model versioning, monitoring and automated testing.Experience deploying AI solutions on cloud platforms such as Azure ...

including machine learning models, data pipelines and application components that are secure, reliable and performant.Drive the operationalisation of AI solutions using modern engineering and MLOps practices, including CI/CD, model monitoring, testing and lifecycle management.Ensure solutions are developed in line with security, privacy, governance and responsible AI requirements, particularly … practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation and evaluation approaches.Experience with MLOps and modern engineering practices, including CI/CD pipelines, model versioning, monitoring and automated testing.Experience deploying AI solutions on cloud platforms such as Azure ...

Senior MLOps EngineerSalary: 70,000 to 100,000, depending on experienceLocation: West LondonWorking arrangement: Predominantly office and customer-site based, with some remote working availableEmployment: Permanent, full-timeMFK Recruitment is recruiting a Senior MLOps Engineer for an innovative UK technology company developing advanced Artificial Intelligence and Machine Learning solutions … five years, and all four are still with the business. This speaks volumes about the company’s culture, technical challenges and long-term opportunities.Senior MLOps Engineer roleThe Senior MLOps Engineer will develop and improve the infrastructure that takes advanced AI and computer vision models from research through to reliable production ...

Head of Engineering and Technical Architect Cloud & Platform Integration: Partner closely with our GCP and Data Engineering teams to build seamless LLMOps/MLOps CI/CD pipelines, ensuring scalable and cost-effective model deployment via Vertex AI and containerized environments. Take ownership of building and maintaining robust LLMOps pipelines. … data warehouse architectures. Hands-on experience with Google Cloud Platform (GCP) services including Vertex AI, BigQuery, Cloud SQL, and Google Cloud Storage (GCS). MLOps/LLMOps Pipelines: Proven track record of architecting pipelines for model deployment, performance tracking, hyperparameter tuning, and containerized workflows using Docker and Kubernetes (GKE/ ...

scale representation learning techniques. Experience working with distributed computing environments, large datasets, and scalable training or inference systems. Knowledge of cloud platforms and modern MLOps practices. Excellent communication skills with the ability to work effectively across technical and non-technical teams. Pragmatic approach to balancing engineering excellence with business outcomes. ...

outputs, assumptions and trade-offs. Good understanding of data engineering, data quality, privacy, ethics and responsible model use. Desirable skills and experience Experience with MLOps, cloud platforms, vector databases, NLP/LLMs or AI-assisted products. Experience mentoring data scientists or setting technical standards within a team. Experience working ...