226 to 250 of 336 MLOps Jobs in the UK

solution lifecycle—assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems. THE WORK Formulate real‐world problems into practical, efficient … Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps & MLOps Customize and apply Deep Learning and Generative AI models for various use cases based on the business needs, data availability, system and infrastructure requirements—including ...

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 ...

solve complex engineering and operational challenges. How you can make an impact Lead the design and evolution of our ML platform, infrastructure and MLOps capability Build and maintain scalable, reliable and secure systems for model training, testing, deployment, monitoring and lifecycle management Develop the infrastructure and tooling that enable … vision with operational rigour, and you’re motivated by delivering usable, secure, and elegant solutions to complex technical problems. Proven experience in a senior MLOps, ML Platform, ML Infrastructure, Platform Engineering or Machine Learning Systems role Strong hands-on background in software engineering and cloud infrastructure, ideally with direct experience ...

currently available globally. The Role We are building custom AI hardware and the full-stack software ecosystem to run it. As our first dedicated MLOps Engineer, you will own the infrastructure that takes models from research to silicon-validated production — designing, building, and operating the pipelines, tooling, and platforms that ...

from design to deployment, ensuring safe, scalable, and measurable outcomes across the business. You will lead a multidisciplinary team of DS, ML engineers and MLOps specialists, embedding governance and risk controls throughout the lifecycle. #J-18808-Ljbffr ...

Account Solution Architect to cover Northern EMEA. This role involves working closely with customers to design and present solutions around ML infrastructure and MLOps workflows. Ideal candidates will have over three years in solutions engineering, strong knowledge of AI frameworks, and excellent communication skills. The position requires ...

involves working collaboratively to define the company's 2026 technical roadmap while solving complex challenges in autonomous systems. The role requires expertise in AI, MLOps, Software Engineering, and Data Science. The company offers a range of benefits, including family-first relocation assistance and full UK visa sponsorship. #J-18808-Ljbffr ...

application, workflow, release and logging remediation within a security assessment remediation programme. The successful contractors will work with AppSec/DevSecOps, QA automation, MLOps, Data/AI Governance, ServiceNow/Jira specialists and the Security Remediation Lead to implement application-level changes that close controls and generate usable evidence. This ...

cases, coordinating their lifecycle from ideation through to optimisation and, where appropriate, decommissioning. Ensure solutions are production‐ready and scalable through the adoption of MLOps, AI guardrails, and emerging capabilities, maintaining long‐term sustainability. Governance, Risk & Regulatory Compliance Define and integrate a comprehensive AI governance, risk, and control framework aligned ...

data platforms for analytics and AI/ML Deep Microsoft Azure expertise Hands‐on experience with Databricks, APIs, and integration platforms Strong understanding of MLOps and productionizing machine learning Experience leading and scaling engineering teams Tech stack: Azure, Databricks, Python, PySpark, SQL, JavaScript, Node, Bash THE ROLE … systems that support analytics, ML workloads, and real‐time operations Create API‐first integration layers for internal teams and external partners Implement MLOps best practices for model deployment and lifecycle management Lead exceptional teams Build, mentor, and scale high‐performing engineering teams Set standards for code quality, security, and performance ...

Operations teams to solve complex business challenges Mentoring and developing a growing team of Data Scientists Establishing best practice across model development, governance and MLOps Tech Stack Python | SQL | TensorFlow | PyTorch | AWS | Azure | SageMaker | NLP | LLMs | MLOps What we're looking for: Strong commercial Data Science and Machine Learning experience ...

that feed our dispute systems. Collaborate with platform and backend engineers to integrate models seamlessly. Experience and qualifications 5+ years of experience as an MLOps/ML Engineer. High proficiency in writing clear, production‐ready Python code. Experience with production ML models (online or offline) and standard MLOps practices. Experience ...

production environment — not just notebooks. You've owned models after they ship and know how to keep them healthy. Full‐Lifecycle Delivery (MLOps): Comfortable delivering the end‐to‐end production lifecycle — model training, versioning, monitoring, and champion/challenger experimentation — without relying on a dedicated ML engineering team to carry … what to do about it. [Bonus] Experience with VertexAI TOOLS & TECHNOLOGIES Languages: Python, SQL Data & Transformation: dbt, Snowflake, BigQuery Visualisation & BI: Looker Engineering & MLOps: Docker, GitHub Workflow & Orchestration: Vertex AI Pipelines (GCP), Kubeflow LLMs & GenAI: Gemini API, Claude API INTERVIEW PROCESS Step 1: People Team Screening Call (30 min) Step ...

engineering standards, and drive high-impact ML products from research to deployment. The role requires deep ML expertise, strong software engineering, and experience in MLOps, distributed systems, and scalable APIs. #J-18808-Ljbffr ...

/ML models, from development to deployment, monitoring and optimisation. You will lead the design of scalable, production‐grade ML systems and establish robust MLOps practices in a governance‐driven environment. You will also drive platform architecture, ensure safety and compliance, and mentor a high‐calibre ML engineering team ...

involves architecting cloud-native systems and leading engineering teams to deliver high-quality solutions using Azure and Databricks. Candidates should possess deep knowledge of MLOps strategies and have hands-on experience in building integrations. This hybrid position offers the opportunity to drive innovation and business impact while fostering a culture ...

ability to drive adoption, influence behaviours, and deliver outcomes at pace Exposure to technologies, modern cloud platforms, customer data platforms, enterprise BI tooling, or MLOps governance environments would be highly advantageous. Why Join? This is an opportunity to define and shape governance strategy during a significant period of enterprise transformation. ...

strongly preferred. Experience writing about complex technical topics for external audiences is required. Experience with AI, GPUs, Kubernetes, networking, datacenter infrastructure, cloud platforms, MLOps, sovereign AI, or enterprise infrastructure is a major plus. Why should you join us? What sets us apart is our blend of modern technology, competitive benefits ...

infrastructure changes. Azure DevOps Pipelines : Design, build, and maintain secure, high‐speed CI/CD pipelines within Azure DevOps to automate code promotion and MLOps workflows. Incident Management : Lead the response, containment, and resolution of critical platform outages, serving as a primary escalation point for high‐priority cloud and infrastructure … requirements, post‐mortems, and engineering strategies effectively to both technical and non‐technical stakeholders. AI/ML Platform Automation : Architect and maintain highly available MLOps platforms across AWS and Azure environments. Developer Enablement : Build self‐service infrastructure tools, deployment templates, and continuous training/inference pipelines to eliminate friction. ...

infrastructure changes. Azure DevOps Pipelines : Design, build, and maintain secure, high-speed CI/CD pipelines within Azure DevOps to automate code promotion and MLOps workflows. Incident Management : Lead the response, containment, and resolution of critical platform outages, serving as a primary escalation point for high-priority cloud and infrastructure … requirements, post-mortems, and engineering strategies effectively to both technical and non-technical stakeholders. AI/ML Platform Automation : Architect and maintain highly available MLOps platforms across AWS and Azure environments. Developer Enablement : Build self-service infrastructure tools, deployment templates, and continuous training/inference pipelines to eliminate friction. ...

technology solutions across UK government departments.Our work has positively influenced the lives of over 40 million UK citizens. Overview We're looking for an MLOps Engineer to build the operational backbone that lets models move safely and reliably from experimentation into production, at scale, across a central government department … integrated environments - Secure-by-design engineering practices appropriate to sensitive public-sector data Desirable Experience - AWS/Azure/GCP infrastructure certifications - Experience building MLOps platforms within regulated or public-sector environments - Familiarity with model governance/traceability requirements such as ATRS - Prior delivery within UK central government ...

optimizing the ML systems that power drug discovery processes, ensuring scalability across vast datasets. The ideal candidate will have hands-on experience in infrastructure, MLOps, and distributed systems, and be excited to work with ML technologies. The position is hybrid, requiring office presence at least 50% of the time. Compensation ...

that combine machine learning, privacy, and software engineering to transform how market research is conducted. This team sits at the intersection of platform engineering, MLOps, distributed systems, and Generative AI. Working alongside researchers, data scientists, and product teams, you'll help scale a platform that supports synthetic data generation, Digital … research. Key Responsibilities • Define and own the technical vision for a large-scale AI platform • Lead and grow a team of Software, Data and MLOps Engineers • Build scalable GCP, Kubernetes, and Vertex AI infrastructure • Establish engineering standards, SDLC processes, and delivery practices • Partner with researchers to productionise advanced ...

expert driving innovation and market-leading practices across multiple clients and industries - Strong understanding of cloud-centric solution design, the full data lifecycle, and MLOps/AIOps - Experience mentoring engineers and architects, building capability in junior team members and client counterparts- You will be required to hold active SC clearance … similar)- Experience with modern data warehouse and lakehouse ecosystems (Redshift, Snowflake, Databricks, BigQuery, Synapse)- Familiarity with SQL and Python or Java - Experience with MLOps and Infrastructure as Code (Terraform, CloudFormation etc.) for data, analytics and AI services - Strong understanding of CI/CD and modern approaches to IT and infrastructure ...

experimentation through to productised, maintainable solutions that deliver measurable value. Drive engineering excellence across ML systems, including CI/CD, testing, observability, reliability, and MLOps guidelines. Define technical standards, patterns, and protocols for ML engineering and applied ML science across teams. Lead complex, multi-team technical initiatives and influence organisational … systems, scalable architectures, and API design. Advanced programming experience in languages such as Python, Go, Java, or C++. Advanced SQL knowledge. Strong experience with MLOps, production ML systems, model lifecycle management, and monitoring. Experience working with large-scale data systems and distributed computing frameworks (e.g. Spark, Hadoop). Knowledge ...