451 to 475 of 708 MLOps Jobs in the UK

internal capability Bonus Points For Prior experience in business development or pre‐sales within a consultancy environment Hands‐on familiarity with modern data science, MLOps or AI operationalisation Knowledge of data ethics, AI governance or analytics operating models Change management or business analysis experience within large transformation programmes Confidence ...

appropriate performance metrics. Experience creating, managing, and interrogating graph databases (e.g., Neo4j). Experience with maritime, aerial, or other remote-sensing imagery. Exposure to MLOps tools (MLflow, Weights & Biases, Ray etc.) Experience deploying systems with containerisation, both on premises and in the cloud (e.g. using Docker and AWS ECS/ ...

appropriate performance metrics. Experience creating, managing, and interrogating graph databases (e.g., Neo4j). Experience with maritime, aerial, or other remote-sensing imagery. Exposure to MLOps tools (MLflow, Weights & Biases, Ray etc.) Experience deploying systems with containerisation, both on premises and in the cloud (e.g. using Docker and AWS ECS/ ...

appropriate performance metrics. Experience creating, managing, and interrogating graph databases (e.g., Neo4j). Experience with maritime, aerial, or other remote-sensing imagery. Exposure to MLOps tools (MLflow, Weights & Biases, Ray etc.) Experience deploying systems with containerisation, both on premises and in the cloud (e.g. using Docker and AWS ECS/ ...

/ML applications in security — threat detection, behavioural analytics, anomaly detection, and predictive risk modelling Knowledge of securing AI systems — including AI pipelines, MLOps practices, data platform security, model registries, and inference endpoints Experience with AI-specific threats and controls: adversarial robustness, data integrity, model theft, and supply chain security ...

Learning Systems Engineer (Distributed Systems) London (1-2 days per week in office) AI Startup £100,000-£110,000 DOE + Bonus Skills: Python, MLops, Pytorch, Grafana, Elastic Search, TensorRT About the Company Our client is a venture-backed technology company building software to optimise large-scale physical infrastructure. Their ...

synthetic data and teleop logs, version them, apply weak‐supervision labelling, curate balanced datasets, and auto‐surface fresh failure cases into retraining. Work with MLOps & Data Platform teams to scale distributed training and optimize models for real‐time edge inference. What We're Looking For 3+ years building deep‐learning ...

What We’re Looking For You’ll be great fit for this role if: Have experience with AI/ML technologies, model deployment, or MLOps environments. Enjoy solving complex technical challenges and improving system performance. Have experience building AI agents, automation solutions, or data processing pipelines. Can work effectively with ...

knowledge/qualifications/experience that suggest you can quickly learn tools and processes which enable the establishment and smooth running of an MLOps and AI delivery organisation in a complex environment #J-18808-Ljbffr ...

cases (forecasting, ATP optimisation, document AI, anomaly detection). Define ML data contracts and embed models in operational processes (Fiori, SAC). Establish MLOps foundations: pipelines, CI/CD, monitoring, retraining, drift. Chair the Data & AI Design Authority, driving alignment across internal teams and multiple SI/vendor partners. Govern ...

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 ...

improving performance, cost efficiency, and security posture. Mentor and guide team members, fostering a culture of technical excellence and continuous learning. Partner with Security, MLOps, and Product Engineering teams to deliver scalable, resilient, and compliant systems. Define agentic patterns to inflect the way we build, deploy, and observe cloud infrastructure. ...

knowledge/qualifications/experience that suggest you can quickly learn tools and processes which enable the establishment and smooth running of an MLOps and AI delivery organisation in a complex environment Security Clearance Due the nature of the work that we do at Thales, many of our roles ...

integration between connected devices, cloud services, data platforms, and engineering teams. As the capability matures, the role will provide a clear development path into MLOps and ML platform engineering, supporting model deployment, model lifecycle controls, ML pipeline automation, and governed promotion of machine learning solutions from development into production. … validation, monitoring, transformation and handover between operational platforms and analytical environments. Proactively identify opportunities to simplify, automate and strengthen digital platform delivery. Growth into MLOps and ML platform engineering Develop capability in MLOps practices such as experiment tracking, model packaging, model registry, model promotion and governed deployment workflows. Support ...

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 ...

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 ...

with data engineers, clinicians and business teams to tailor solutions to client needs Deploy AI and machine learning models in production environments using established MLOps and LLMOps practices Use cloud platforms and data solutions to ensure scalability and operational integrity Present data-driven recommendations to senior audiences, demonstrating the impact … learning techniques such as NLP and deep learning, applied to biomedical data Knowledge of cloud technologies (Azure, AWS or GCP) and model deployment using MLOps frameworks Strong programming skills in Python and SQL with experience in frameworks such as PyTorch, TensorFlow and Hugging Face Experience using data platforms ...

personal to all of us.” – Julie Sweet, Accenture CEO. We are a dynamic team of specialists in Data Science, Data Engineering, and MLOps, dedicated to delivering cutting‐edge AI solutions within secure government and defence environments.Join us to be part of an inclusive and collaborative environment where innovation thrives … professional growth and career advancement, our department fosters entrepreneurial thinking and drives innovation by constantly seeking new business opportunities. As a Consultant in MLOps you will: Be engaged at the forefront of technological advancements in GenAI and expected to keep up to date with latest trends Build and/ ...

Machine Learning and Generative AI solutions in production environments. Work with modern AI frameworks, LLMs, RAG, prompt engineering and vector databases. Ensure robust MLOps practices, APIs, data pipelines and modern software engineering disciplines are in place. Strategic & Stakeholder Engagement Act as a thought leader, willing to challenge the business … Machine Learning and Azure Data Platform technologies. Knowledge of LLMs, RAG, prompt engineering, vector databases and modern AI frameworks. Experience with APIs, data pipelines, MLOps practices and modern software engineering disciplines. Experience managing partner-led delivery and a mix of onshore/offshore teams. Microsoft certifications (e.g., Azure AI Engineer ...

driven systems that perform reliably in production and drive conversion. You'll work alongside a multi-skilled group of data scientists, AI engineers and MLOps specialists in cross-functional teams. We deliver against quarterly OKRs, own our work end to end, and put collaboration at the heart … Solid grounding in statistics and ML theory across supervised and unsupervised learning, NLP (entities, intent), recommendation, prediction and uplift modelling Full model lifecycle and MLOps: containerisation (Docker/ECR) and deployment on AWS Working with large text datasets and data pipelines Nice to have: sales psychology applied in data products ...

technical and non-technical audiences. Demonstrated capability to guide engineering teams and influence technical strategy. Some other highly valued skills may include: Experience with MLOps platforms such as Databricks or SageMaker, and familiarity with hybrid cloud strategies (Azure, on-prem Kubernetes). Strong understanding of AI infrastructure for scalable model … e.g., LangChain, AutoGen) and Model Context Protocol (MCP) for building autonomous AI workflows and interoperability. Awareness of emerging trends in GenAI platforms, open-source MLOps, and cloud-native AI solutions You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change ...

managing token, inference, and infrastructure spend so solutions stay cost effective as they scale. Integrate AI solutions with enterprise data systems, APIs, and MLOps/LLMOps tooling, applying sound system design and distributed‐systems judgment. Apply responsible‐AI judgment proportionate to the risk of each use case, working with risk … example pgvector, Pinecone, Weaviate, or Chroma) and agent or orchestration frameworks (for example LangChain, LlamaIndex, or the Model Context Protocol). Experience with MLOps/LLMOps tooling such as experiment tracking, model versioning, monitoring, evaluation/observability platforms, or CI/CD for ML and LLM systems. Experience implementing responsible ...

Job title: ML Systems Engineer - Model Training and Infrastructure (SWE-focused LLMs) Location: London; full in-office working as default Start date: ASAP Compensation: £80,000 - £110,000 Base Salary & £80,000 - £110,000 Share ...

MLOps Technical Manager Who is Parser? Technology alone does not create impact-the right teams do. Founded in 2018, Parser is a boutique technology services and consulting firm helping global organisations solve complex business challenges through digital transformation, product development and Al enablement. We are a fast-growing team … tier specialists in a truly global environment, we'd love to meet you. How will you impact? As a Tech Lead with a strong MLOps engineering background, you will lead the design, architecture, and delivery of ML infrastructure, owning the end-to-end stack from backend to frontend while driving ...

partner with client teams, lead design sessions, and drive reusable patterns and standards that scale across engagements. The role emphasizes production readiness, LLM orchestration, MLOps and cost governance, with direct pathways to advanced enterprise projects and partnerships. #J-18808-Ljbffr ...