276 to 300 of 435 MLOps Jobs in London

Databricks seeks a senior technologist to architect production-grade ML and AI workloads, spanning end-to-end pipelines, training/inference optimization, and MLOps lifecycle management with cloud-native integration. You will lead GenAI initiatives, advise solution architects during pre-sales and post-sales cycles, influence the AI roadmap ...

guide enterprise customers in building production-grade ML and AI applications on the Databricks Data Intelligence Platform. You will mentor colleagues and advance GenAI, MLOps, and LLMOps expertise while shaping the platform roadmaps. You will partner with field engineers and Solution Architects to deliver end-to-end AI solutions, strong ...

colleagues. You will work with solution architects, lead GenAI initiatives, and influence the AI roadmap while maintaining cutting-edge expertise in areas like GenAI, MLOps, and LLMOps. #J-18808-Ljbffr ...

evolve the backend platform supporting their AI services, ensuring reliable operations for local authority clients. The ideal candidate has strong Python skills, experience in MLOps, and a solid background in Azure-native technologies. This hybrid role is based in London, requiring office attendance at least 1-2 days a week. ...

services, while guiding the technical direction for enterprise-scale backend services. You will build scalable backend services, data pipelines, and platform components, champion MLOps #J-18808-Ljbffr ...

model performance, with strong object-oriented programming, machine learning and statistical skills, and experience taking models into production, designing ML pipelines and working with MLOps, CI/CD and Azure. Key Responsibilities Delivery of data science products Leading data science projects end-to-end, from problem framing through development, deployment … support the business with proactive analytics and insights. Using generative AI to enrich insight and unlock new opportunities, deployed and maintained through the same MLOps patterns applied to traditional models. Engineering and MLOps standards Designing, building and maintaining machine learning pipelines in a cloud environment, applying sound software engineering practice. ...

/UX and graphical/web design Nice to Have Experience with Python or Rust Familiarity with SQL Exposure to DevOps practices Experience with MLOps or AI infrastructure What they will be looking for: Problem Solver - You love solving challenging problems (proven history of doing so) Ownership & Intensity - You take ...

image classification, object detection and segmentation tasks. Experience creating clear documentation and annotation guidelines. Excellent organisational skills. Desirable Experience with PyTorch datasets. Experience with MLOps or data pipelines. Understanding of computer vision model training. Knowledge of active learning workflows. Experience with Git. Robotics or autonomous systems experience. What ...

image based AI models, density and object-based identification o Experience with AI/ML platforms and processes: OpenVINO or similar toolkit; MLOps training pipeline; SageMaker. Requires experience of data governance, privacy policies and AI assurance methods Requires indepth AWS experience, particularly S3, serverless computing (Lambda), EventBridge/SNS/ ...

master the stack from pytorch based learning libraries to complex data networking and GPU utilisation. We're looking for an experienced AI Infrastructure or MLOps Engineer who has already built and operated production AI systems rather than someone at the beginning of their career. You'll have strong experience with ...

production efficiency and latency requirements; Write clean, well‐tested and well‐documented code and uphold engineering standards across the team; Lead model handovers to MLOps engineers with documentation covering capabilities, known limitations, failure modes and retraining criteria; Stay current with advances in ML engineering, distributed training and biomedical AI tooling. ...

opportunities. Deep expertise across enterprise data domains, including data strategy, governance, privacy, analytics and AI transformation. Strong understanding of data science, AI, Generative AI, MLOps, business intelligence, responsible AI, AI governance and modern analytics operating models, with the ability to translate emerging technologies into business value. Proven experience leading complex ...

organisations. Previous consulting or advisory experience within a professional services environment at Principal Consultant or equivalent level. Familiarity with AI governance, model risk management, MLOps, responsible AI frameworks, or regulatory considerations relating to AI deployment. Experience building senior client relationships, contributing to business development activities, or supporting proposition and capability ...

engineering standards. Design and run large-scale distributed training on multi-node GPU clusters; drive throughput, stability, and cost efficiency in partnership with MLOps & Data Platform teams. Define what pretraining-scale data looks like: partner with the Data Collection team and external data providers to secure a steady supply ...

senior member of the AI Enablement leadership team, contributing to the team's overall direction alongside the Senior Staff Data Engineer and Senior Staff MLOps Engineer. This is a unique opportunity to be part of a critical strategic initiative for a pharmaceutical company that invests heavily in research and development ...

senior member of the AI Enablement leadership team, contributing to the team's overall direction alongside the Senior Staff Data Engineer and Senior Staff MLOps Engineer. This is a unique opportunity to be part of a critical strategic initiative for a pharmaceutical company that invests heavily in research and development ...

ensure evaluation methods are reliable, identify gaps, and drive new methodology for evaluating our models. Stay up to date with the latest in MLOps practices and tools and bring improvements into the workflow. About you In order to set you up for success as a Staff Machine Learning ...

core levers (telecoms, ISP, utilities, media, fintech or insurance) Working knowledge of modern data stacks and ML delivery (data lakes and warehouses, feature pipelines, MLOps, CDPs, decisioning platforms) sufficient to shape scope and challenge trade-offs with engineers and scientists Telecoms or ISP experience, and/or experience ...

applications using Generative AI, Large Language Models and orchestration frameworks. Write high-quality Python code and contribute to cloud-native applications and services. Apply MLOps best practices, including CI/CD, containerisation, monitoring and observability. Partner with data scientists, engineers and business stakeholders to translate business challenges into impactful … orchestration frameworks. Strong Python programming skills and understanding of modern backend architectures. Experience working with cloud platforms and production-grade AI systems. Knowledge of MLOps, CI/CD, containerisation and model monitoring. Experience building data pipelines for model training, fine-tuning and inference. Solid grounding in machine learning, statistics ...

agentic workflow capabilities for legal content products. In addition to writing code on complex systems, this position provides technical direction on architecture, MLOps, responsible AI, legacy system integration, AWS-based delivery, and AI-assisted development practices. The position does not have direct reports. Key Responsibilities: Serve as the initial point … accuracy, groundedness, citation quality, hallucination risk, agent task success, latency, cost, reliability, and business value. Successfully implement development processes, coding best practices, code reviews, MLOps practices, and responsible AI controls. Apply AI-assisted development tools to reduce software development cycle time and support code explanation, test generation, refactoring, debugging, documentation ...

build, testing, deployment, monitoring and handover. This is a senior, hands‐on delivery role for someone who can work independently across architecture, integration, DevOps, MLOps, AIOps, data engineering and governance. You will make technical decisions, solve complex integration challenges and ensure AI solutions are reliable, scalable and safe … Landing Zone sandbox to test technical options, demonstrate value and provide clear go/no-go recommendations before full delivery. DevOps, MLOps and AIOps ownership: Implement and maintain CI/CD, monitor and release pipelines using Azure DevOps, including version control, rollback capability, automated testing and production health monitoring. Documentation ...

applications on the Databricks Data Intelligence Platform. You will also continue to sharpen your technical expertise in cutting‐edge areas like GenAI, ML, MLOps, and LLMOps, while mentoring colleagues and establishing yourself as an AI thought leader. Impact you will have Architecting Workloads: Design and implement production-level … workloads, including end‐to‐end pipelines, training/inference optimization, MLOps lifecycle management, and integration with cloud‐native services. GenAI Leadership: Serve as a practitioner for enterprise GenAI solutions, specializing in RAG architectures, agentic systems (including tool‐calling, multi‐agent orchestration, and guardrails), AI observability, and natural language querying ...

applications on the Databricks Data Intelligence Platform. You will also continue to sharpen your technical expertise in cutting-edge areas like GenAI, ML, MLOps, and LLMOps, while mentoring colleagues and establishing yourself as an AI thought leader. Impact you will haveArchitecting Workloads: Design and implement production-level … workloads, including end-to-end pipelines, training/inference optimization, MLOps lifecycle management, and integration with cloud-native services. GenAI Leadership: Serve as a practitioner for enterprise GenAI solutions, specializing in RAG architectures, agentic systems (including tool-calling, multi-agent orchestration, and guardrails), AI observability, and natural language querying ...

seeking a ML Ops Engineer to join our Platform Engineering team at Anaplan. In this role, you will design, scale, and maintain high-performance MLOps and LLMOps infrastructure supporting our cutting-edge AI-infused scenario planning platform. You will work closely with Data Scientists, ML Engineers, and Cloud Infrastructure teams … compute workloads, high-speed networking, and storage for efficient model training and low-latency inference. Build and maintain robust CI/CD and MLOps pipelines for continuous model training, evaluation, packaging, and production deployment. Deploy Large Language Models (LLMs) and generative AI workloads using advanced inference engines (e.g., Triton Inference ...

part of the Data and AI platform team; you'll get to pioneer on real world problems, bringing your knowledge of AI/ML, MLOps and LLMs to bear - collaborating cross team to make your vision a reality. You'll be backed by our platform team, and have a wealth … scientific evaluation with the operational maturity to champion high-value applications and confidently push back on unsuitable AI use cases. Design, refine and build MLOps component of the data and AI platform, from Vector Databases through feature stored and model serving, all at the millisecond scale. Implement CI/ ...