276 to 300 of 581 MLOps Jobs in London

facing sales activitiesData governance & compliance - Strong background in security frameworks, regulatory compliance (GDPR), data lineage, and quality managementAI/ML integration capabilities - Experience with MLOps, analytics platforms, and integrating AI/ML into data architecturesAgile delivery & thought leadership - Proven agile/hybrid delivery experience with contribution to practice growth through ...

knowledge of modern AI, cloud, and enterprise technologies, with the ability to rapidly learn, evaluate, and adopt emerging technologies.Experience with containerization, CI/CD, MLOps/LLMOps, observability, and secure-by-design engineering practices.Demonstrated ability to leverage AI-assisted development and intelligent engineering tools to accelerate solution delivery.Excellent consulting, communication ...

generation, environment design, mid-training, supervised fine-tuning, offline reinforcement learning, online reinforcement learning, reward modelling, transition modelling, etc. Our team also has dedicated MLOps, Infra and Inference support at scale. We focus on improving the long horizon, goal-conditioned instruction-following of large models for GUI/Computer ...

Master’s or Ph.D. in a quantitative or technical field (e.g. Mathematics, Statistics, Computer Science). Nice to Have: Familiarity with production environments, MLOps, or data pipelines. Experience working with large-scale data using PySpark or equivalent distributed data processing tools. Experience in gaming, e-commerce, or subscription-based products.Benefits ...

required to prevent recurrence. Deep expertise in Kubernetes, alongside experience operating infrastructure across hybrid on-premises and cloud environments. Experience building, running or evolving MLOps infrastructure, ideally including notebook environments such as Kubeflow, GPU compute for distributed training and model serving. Familiarity with batch compute for data-intensive scientific workloads ...

tools, job control, review) that make ML/automation workflows intuitive and accessible.Collaborate with global stakeholders and architects to implement cost-effective data and MLOps pipelines; document methodologies.Build, package, and configure complex software systems across Linux.Improve efficiency, stability, and observability through profiling, metrics, and tracing.Validate work with methodical testing (unit ...

Azure Data)Data governance & compliance - Strong background in security frameworks, regulatory compliance (GDPR), data lineage, and quality managementAI/ML integration capabilities - Experience with MLOps, analytics platforms, and integrating AI/ML into data architecturesTechnical leadership at scale - Leading 15+ person cross-functional teams and serving as technical escalation point ...

control, review) that make ML/automation workflows intuitive and accessible. Collaborate with global stakeholders and architects to implement cost-effective data and MLOps pipelines; document methodologies. Build, package, and configure complex software systems across Linux. Improve efficiency, stability, and observability through profiling, metrics, and tracing. Validate work with methodical ...

including an understanding of performance, scaling and system architecture Strong programming skills in Python, with familiarity with ML frameworks and development workflows Experience with MLOps or production-oriented workflows, including environment management, reproducibility and deployment considerations Nice to have Experience training or optimizing ML systems Experience solving optimisation/MILP ...

machine learning, or a related field Authored publications in top‐tier journals and conferences (e.g. NeurIPS, ICLR, ICML, EMNLP) Experience working with MLOps infrastructure or deploying AI models to production, including the associated monitoring, testing and quality assurance Experience working with AI in regulated environments Created and optimised state ...

Event Hubs, or Kinesis for real-time data processing Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines Experience processing and managing unstructured data types (text, images, logs, sensor data) Understanding of Lambda and Kappa architectural patterns and when to apply each ...

Event Hubs, or Kinesis for real-time data processing Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines Experience processing and managing unstructured data types (text, images, logs, sensor data) Understanding of Lambda and Kappa architectural patterns and when to apply each ...

clients' AI ambitions and business outcomes into a hardware and platform roadmap, positioning NTT DATA's end-to-end portfolio — silicon, systems, storage, fabric, MLOps stack and managed services — to land service-led AI solutions. Lead integration of compute, storage, networking, the AI software stack (CUDA, ROCm, Triton, NIM, NVIDIA ...

helping organisations solve complex operational, technical and regulatory challenges through AI adoption at scale.You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications.Key responsibilities:·Building … Using Python and SQL to build robust, scalable AI and data solutions·Working with cloud platforms such as AWS, Azure, GCP or Databricks·Supporting MLOps, LLMOps, CI/CD and software engineering best practice·Collaborating with technical and non-technical stakeholders across complex programmes·Helping identify technical, delivery, security, data ...

maintain platform capabilities for model training, feature engineering, deployment and observability across cloud and on-prem environments. Build CI/CD pipelines for ML (MLOps) including automated testing, packaging, model registry workflows and promotion across environments. Implement containerised deployments (Docker/Kubernetes) and orchestration for batch and real-time inference … Strong software engineering skills in Python and/or Java/Scala, with clean coding, testing and code review practices. Hands-on experience with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, Databricks, or equivalent. Proven experience with Kubernetes, Docker, Helm and infrastructure as code (Terraform/CloudFormation). ...

delivery of AI projects end to end from the silicon and data center design that underpins AI workloads, through the software and MLOps stack, to the governance frameworks that make AI trustworthy and defensible at scale. This is a technical hardware-and-software architect role, not a strategy-only position. … interconnects ,parallel/high-throughput storage, and orchestrationDesign the AI software stack: training and fine-tuning pipelines, distributed training frameworks, inference/serving platforms, MLOps/LLMOps tooling, vector databases, and retrieval-augmented generation (RAG) and agentic architectures. Define and AI governance frameworks covering model risk management, responsible AI, data ...

Senior ML Engineer will own the journey from experimentation and hypothesis testing through to secure, production-grade deployment, using a modern AWS-based MLOps and LLMOps platform. The Role The successful candidate will balance rapid experimentation with production readiness, prototyping and validating machine learning and generative AI approaches while ensuring …/B testing and statistical evaluation Proven experience moving models from experimentation into production with appropriate governance and quality controls Hands-on experience with MLOps tooling such as MLflow, Weights & Biases or Data Version Control Practical experience building LLM/GenAI applications, including prompt engineering and retrieval-augmented generation ...

deployment of production-grade AI systems tailored to audit applications. Ensure solutions are scalable, reliable, and maintainable by applying strong software engineering principles, MLOps practices, and cloud-native development.· End-to-End AI Solution Delivery: Oversee the full lifecycle of AI product engineering—from architectural design and prototyping … Databricks, MLflow, LangChain and LangGraph. Champion automation, testing, and observability across pipelines.· Operational Excellence: Define reusable development patterns, enforce coding standards, and promote MLOps best practices that support version control, performance optimisation, and maintainability.· Cross-Disciplinary Collaboration: Partner closely with data scientists, product managers, platform engineers, and QA teams ...

delivery of AI projects end to end from the silicon and data center design that underpins AI workloads, through the software and MLOps stack, to the governance frameworks that make AI trustworthy and defensible at scale.This is a technical hardware-and-software architect role, not a strategy-only position. … interconnects ,parallel/high-throughput storage, and orchestrationDesign the AI software stack: training and fine-tuning pipelines, distributed training frameworks, inference/serving platforms, MLOps/LLMOps tooling, vector databases, and retrieval-augmented generation (RAG) and agentic architectures.Define and AI governance frameworks covering model risk management, responsible AI, data lineage ...

enterprise applications and workflows.Oversee the full technical lifecycle, from solution design and model selection through to deployment, monitoring and continuous improvement.Design and implement robust MLOps and LLMOps practices, including CI/CD, model monitoring, evaluation and governance.Deploy and optimise models using cloud-based AI services such as AWS Bedrock, Azure … tooling such as LangChain, LangGraph or similar open-source AI toolkits.Experience fine-tuning, evaluating, deploying and monitoring large-scale AI systems.Strong understanding of MLOps and/or LLMOps, including CI/CD, model deployment, monitoring, evaluation and governance.Experience designing AI systems with a strong focus on security, responsible AI, ethical ...

delivery of Generative AI solutions, including RAG architectures, prompt engineering, and integration with Azure AI services (e.g., Azure OpenAI, Azure AI Search).Ensure robust MLOps practices are followed, including model versioning, testing, deployment pipelines, and monitoring of deployed solutions for performance and drift.Champion engineering best practices across the team, including … data processing. Familiarity with Generative AI concepts and tooling, including working with LLMs, prompt engineering, RAG patterns, and vector search. A solid understanding of MLOps principles, including CI/CD for models, automated testing, and monitoring of deployed solutions. Cloud platform experience, preferably Azure, including services such as Azure OpenAI ...

Generative AI solutions, including RAG architectures, prompt engineering, and integration with Azure AI services (e.g., Azure OpenAI, Azure AI Search). Ensure robust MLOps practices are followed, including model versioning, testing, deployment pipelines, and monitoring of deployed solutions for performance and drift. Champion engineering best practices across the team, including … data processing. Familiarity with Generative AI concepts and tooling, including working with LLMs, prompt engineering, RAG patterns, and vector search. A solid understanding of MLOps principles, including CI/CD for models, automated testing, and monitoring of deployed solutions. Cloud platform experience, preferably Azure, including services such as Azure OpenAI ...

demands a Master's or PhD in a quantitative field, requiring strong skills in statistics and machine learning, including extensive experience with Pytorch and MLOps tooling. You will build scalable Data Science capabilities and collaborate with engineers to deploy Machine Learning services. This opportunity blends research and engineering, ideal ...

applications. You’ll drive end-to-end development from discovery to production, work across voice, vision, and text, and leverage LangChain, LlamaIndex, and modern MLOps on AWS/Azure/GCP to deliver scalable, observable AI solutions at scale. #J-18808-Ljbffr ...

products used by millions of customers every day. This is a highly collaborative role where you’ll partner with Product Managers, Engineers and MLOps teams to take ideas from experimentation into production. You’ll also help shape technical best practice across the team, championing robust experimentation, high-quality code ...