Latest mlops Jobs

Spotlight

ML Runtime Engineer (Mid-Level and Senior)

Design and develop high-performance ML runtime systems for AI accelerators, integrating with open-source frameworks like PyTorch and vLLM. Work closely with hardware and software teams in a co-design environment to optimize inference performance. Build low-level runtime components in Rust and contribute to the full stack of ML inference infrastructure.

Fractile London, United Kingdom

Hybrid Permanent

MLOps Platform Developer / Full-Stack AI Engineer

Develop and maintain a full-stack MLOps platform integrating React/TypeScript web applications, PostgreSQL telemetry databases, and LLM serving infrastructure. Manage end-to-end production systems including data pipelines, MQTT ingestion from building management systems, and LoRA fine-tuning on GPU hardware. Work closely with real-world engineering systems in the energy transition sector, optimising heat networks and building services through tailored LLMs and AI-assisted development.

Bluetown London, United Kingdom

Senior MLOps Engineer

Develop and maintain MLOps infrastructure to productionise advanced AI and computer vision models, from distributed training to deployment on cloud and GPU-accelerated edge devices. Work closely with research and engineering teams to build scalable CI/CD pipelines, model registries, and monitoring systems. Operate in high-assurance environments with exposure to defence and security applications.

MFK Recruitment Brentford, London, TW8 9DE, United Kingdom £75,000 – £100,000 pa

Hybrid Permanent Clearance Required

Machine Learning Engineer

This role involves deploying and managing machine learning models in production using Azure Machine Learning, with a focus on building and maintaining scalable MLOps infrastructure. The engineer will design CI/CD pipelines for ML artifacts, implement monitoring and security controls, and support real-time inference workloads. Collaboration with data scientists, developers, and architects is key to optimizing model performance and platform reliability.

Queen Square Recruitment Wokingham, Berkshire, United Kingdom £460 pd

Senior Specialist Solutions Engineer (AI/ML)

Design and implement production-grade machine learning and GenAI solutions on Databricks' platform, with a focus on MLOps, RAG architectures, and LLM deployment. Provide technical leadership during sales cycles by building MVPs, guiding architectural design, and mentoring teams. Create tutorials, lead hackathons, and drive platform adoption through thought leadership in AI/ML innovation.

Databricks London, United Kingdom

On-site Permanent

Senior Specialist Solutions Architect (AI/ML)

Design and implement production-grade machine learning and AI workloads on the Databricks platform, with a focus on GenAI, MLOps, and LLMOps. Lead technical engagements with enterprise customers, build end-to-end AI pipelines, and provide expert guidance on RAG architectures, agentic systems, and AI observability. Mentor internal teams and influence product direction by representing customer needs in AI roadmap discussions.

Databricks London, United Kingdom

Hybrid Permanent

Enterprise Architect - AI

This role involves defining and evolving enterprise architecture strategies with a focus on AI, cloud-native systems, and digital innovation. The architect will design scalable AI and data platforms, lead technical direction across cloud and microservices environments, and translate complex technologies into strategic roadmaps. Key responsibilities include assessing emerging trends like Agentic AI and vector databases, advising senior leadership, and establishing reusable architectural patterns across large-scale transformation programmes.

PRACYVA United Kingdom £550 – £600 pd

Staff ML Engineer | | London |

This role involves shaping the technical direction of AI engineering across an enterprise, focusing on Agentic AI and production-grade RAG systems. You'll establish engineering standards, design scalable vector retrieval strategies, and lead best practices in MLOps, deployment, and AI governance. The position requires strong influence skills to guide multiple engineering teams in building robust, observable, and secure AI solutions.

WeDoTech Bunhill, London, United Kingdom £750 – £900 pd

Hybrid Contract

Lead AI Engineer

This role involves designing and implementing AI solutions to improve operational efficiency, defining LLM architecture, and building AI tools like assistants and workflow automation. You will work within an Azure cloud environment, applying best practices in MLOps and DevOps, and collaborate closely with product teams and senior leadership.

Harnham - Data and Analytics Recruitment London, United Kingdom £85,000 – £95,000 pa

Hybrid Permanent

AI Engineer

Design and deploy scalable AI and machine learning systems, from concept to production, with a focus on Generative AI and LLM-powered applications. Collaborate with data scientists and engineers to build cloud-native, production-grade solutions using MLOps practices. Work on high-impact projects involving orchestration frameworks, model monitoring, and responsible AI deployment.

Harnham - Data and Analytics Recruitment London, United Kingdom £80,000 – £85,000 pa

Machine Learning Ops Engineer

This role involves designing, deploying, and maintaining machine learning models in production using Azure Machine Learning Studio, with a focus on MLOps practices such as automated retraining, model monitoring, and pipeline integration. The engineer will collaborate with actuarial and analytics teams to improve predictions in areas like longevity and investment risk, while building scalable data pipelines using Python, SQL, and Azure Data Factory. A strong emphasis is placed on CI/CD, model lifecycle management, and translating technical outputs into actionable business insights.

Proactive Appointments London, United Kingdom £45,000 – £60,000 pa

Remote Permanent

Senior Machine Learning Engineer

Senior Machine Learning Engineer | Cambridge / Hybrid | £80,000–£120,000 + BonusJoin a fast-growing FinTech/InsurTech company in Cambridge that is transforming how financial and insurance products are built using machine learning and data-driven decision-making.Their platform leverages advanced ML models to...

Platform Recruitment Cambridge, United Kingdom

Senior Machine Learning Engineer

Design and deploy production-grade machine learning and generative AI systems for national security applications, using AWS and modern MLOps/LLMOps practices. Lead model development from experimentation to deployment, with a focus on scalability, security, and responsible AI. Collaborate with data scientists and engineers in a high-impact technical consultancy environment.

eFinancialCareers London, United Kingdom £75,000 pa

Hybrid Permanent Clearance Required

Solution Architect, Local Government AI

The role involves working closely with government clients and partners to design and deploy AI-driven solutions that address public sector challenges in areas like health, safety, and civic services. You'll develop technical strategies, create educational resources, lead proof-of-concept initiatives, and translate mission goals into scalable AI implementations using NVIDIA's hardware and software stack. The position emphasizes collaboration across global teams and ecosystems, with a focus on computer vision, generative AI, and MLOps-enabled deployments.

NVIDIA Spain

Remote Permanent Clearance Required

Solution Architect, Local Government AI

The role involves guiding government clients in adopting AI to enhance public services, by designing and demonstrating technical solutions using NVIDIA's AI platforms. You'll create educational resources, support proofs of concept, and collaborate with technical teams on deployment. The position emphasizes mentorship, product advocacy, and translating public-sector challenges into scalable AI workflows.

NVIDIA

Remote Permanent

Platform Engineer

This role involves designing and maintaining the MLOps and deployment infrastructure that enables data scientists to transition machine learning models from exploration to production. The engineer will work across AWS, Azure, and GCP to build scalable, containerised systems using Kubernetes and infrastructure-as-code tools. The focus is on creating reliable, secure, and high-performance platforms that support client-facing AI solutions.

Faculty AI London, United Kingdom

Hybrid Permanent