276 to 300 of 747 MLOps Jobs in England

platforms Partner with business, technology, and risk stakeholders to align platform capabilities with enterprise priorities Shape platform strategy and technical roadmap, evaluating emerging AI, MLOps, and cloud technologies Ensure delivery outcomes by tracking performance metrics, managing risks, and driving adoption of platform capabilities Required Skills Strong Python engineering expertise with ...

communication skills, able to explain technical decisions clearly to non‐technical stakeholders. Preferred Skills: Experience with recommender systems or personalisation use cases. Familiarity with MLOps concepts and production ML practices. Demonstrated ability to raise technical standards through influence rather than authority. Experience in an e‐commerce or retail environment. CLOSING ...

frameworks such as TensorFlow/PyTorch. Proficiency with Python and strong software development background. Knowledge and experience with AWS is highly desirable. Experience with MLOps practices, including versioning, deployment and monitoring of models highly desirable. Ability to communicate complex technical concepts clearly to non‐technical stakeholders. Why Work for Proximie ...

with Agile software delivery at scale.Excellent communication and stakeholder-management skills, with fluent English (written and spoken).Preferred Experience and/or QualificationsFamiliarity 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 ...

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 ...

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 ...

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 ...

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 ...