26 to 45 of 45 MLOps Jobs in Central London

virtual assistants through advanced prompt engineering and agent orchestration 🔹 Integrate AI applications with SQL, NoSQL, Vector Databases, Knowledge Graphs, and third-party systems 🔹 Implement MLOps best practices and contribute to CI/CD pipelines using Docker, Kubernetes, and Cloud Platforms 🔹 Collaborate with Data Scientists, Architects, Product Managers, and Engineering teams … expertise in: Prompt Engineering Conversational AI NLP Applications AI Agent Development ✔ Experience building scalable APIs using FastAPI ✔ Strong understanding of: HTTP & gRPC Docker & Kubernetes MLOps & AI Deployment Cloud AI Services (AWS, Azure, or GCP) ✔ Experience deploying production-grade AI solutions on enterprise platforms ⭐ Nice to Have ✔ Experience with Vector Databases ...

particularly within the YOLO family. Familiarity with model optimization techniques such as quantization and pruning, and deployment frameworks like TensorRT and OpenVINO. Experience with MLOps tools and practices, including version control (Git), Docker, and CI/CD with GitHub Actions. Excellent problem-solving skills and the ability to perform ...

such as SuperSet, Tableau or PowerBI is a bonus) Hands-on experience in machine learning model development, evaluation, and production deployment, with familiarity in MLOps principles to build scalable and standardised workflows and implement effective ML monitoring systems Proven ability to create polished presentations and effectively communicate insights to customers ...

practices Developing long-term relationships with candidates from leading AI research labs and companies Typical Roles You’ll Recruit For Research Engineers Research Scientists MLOps Engineers Data Scientists AI/ML Engineers What We’re Looking For Proven experience in recruiting for Data, AI, or highly technical domains Strong track ...

About Us: Solirius Reply, part of the Reply Group, delivers technical consultancy and application delivery to our clients in order to solve real world problems and allow our clients to respond to an ever-changing ...

About the Role This role is based at Depixen’s London Office . Depixen is a London-based technology company building the digital decision infrastructure of the construction industry. As a corporate member of the ...

Azure AI services) Lead the productionisation and industrialisation of AI use cases across business functions Manage hybrid teams combining internal engineers, AI Ops/MLOps capability, and third-party delivery partners Partner with senior stakeholders to drive AI adoption, value realisation, and organisational change across a complex enterprise environment ...

infrastructure every pricing professional aspires to work with: High-quality, accessible data A fast, flexible rating algorithm deploy changes in hours Machine Learning Operations (MLOps) that enable fast, transparent, and controlled model development An operating model that gives complete autonomy to pricing professionals to dream up an idea ...

biological plausibility, calibration, and model reliability Collaborating closely with computational biologists and research scientists to integrate models into discovery workflows Driving best practices across MLOps, experimentation infrastructure, and model deployment What They're Looking For Essential 5+ years experience building advanced machine learning systems in production Strong background in deep ...

solutions from development through to deployment and monitoring * Building scalable Generative AI and Agentic AI solutions, including RAG pipelines and orchestration frameworks * Implementing MLOps frameworks, governance and best practices * Translating business requirements into cloud-native AI and data architectures across Azure, AWS and GCP * Collaborating with technical and non-technical … stakeholders to deliver measurable business value * Supporting innovation initiatives, reusable assets, thought leadership and client proposals Candidates should have strong experience in AI Engineering, MLOps and cloud-native AI platforms, alongside hands-on knowledge of technologies such as LangChain, LlamaIndex, MLflow, Kubernetes, Docker and CI/CD tooling. Applicants will ...

supporting organisations as they move from strategy and experimentation through to enterprise deployment. You will work closely with AI Engineers, Data Scientists, Enterprise Architects, MLOps teams, business stakeholders and senior leadership to design, deliver and scale AI solutions that drive measurable business outcomes. Key responsibilities: Translating business objectives into … prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps, LLMOps and model lifecycle management principles Experience designing APIs and integrating AI solutions into enterprise environments Strong understanding of modern data architectures and platform design ...

learning engineering and an ability to influence the adoption of AI within the organization. The ideal candidate should have a strong background in Python, MLOps, and deep learning practices, with a focus on operational excellence and software quality. Opportunities for mentoring and collaborative work in a fast-paced environment await ...

design, build and deploy advanced NLP and LLM-based solutions, taking models from research through to production. You’ll work closely with AI, data, MLOps and product teams to translate business and regulatory requirements into scalable, reliable AI systems. This is a hands-on role for someone who enjoys owning … data preprocessing pipelines Monitoring, optimising and maintaining deployed models for performance, cost and reliability Implementing explainability, fairness and bias-mitigation strategies Collaborating on MLOps pipelines, CI/CD workflows and production deployments Mentoring junior engineers and promoting best practices across the team Staying current with advances ...

better systems that deliver real business value. Key Responsibilities Technical Leadership & Ownership (Individual Contributor) Act as the technical lead for Machine Learning Engineering and MLOps across London Market. Technically lead the most complex and business‐critical ML systems, from architectural design through to production operation. Define and evolve production … experience as a senior or principal Machine Learning Engineer delivering production ML systems at scale. Proven track record of owning or shaping ML platforms, MLOps frameworks, or critical ML infrastructure. Experience operating in complex, cross‐functional environments (insurance or financial services experience is advantageous but not essential). Technical Expertise ...

accuracy and relevance Optimising and shipping large language and multi-modal models into production, balancing performance, latency, and reliability at enterprise scale Developing robust MLOps pipelines and full-stack applications that underpin scalable, production-ready AI deployments Acting as a trusted advisor to clients and internal teams on GenAI strategy … operating at scale Solid Python engineering skills, with a proven ability to build and ship backend systems and APIs Hands-on knowledge of MLOps, cloud-native infrastructure, and the observability practices that keep AI systems performing in the real world Comfortable leading technical teams and bridging the gap between engineering ...

ML Ops Engineer Role Overview Were hiring an ML Ops Engineer to own the reliability, scalability, and operational integrity of our machine-learning systems in research & production. This role sits at the intersection of data ...

We're working with a fast moving tech business looking for a Senior ML Engineer to own personalisation end to end. This isn't a research role. You'll be shipping models to production, building ...

About the Team : You'll be joining the team leading Entrust's Identity portfolio, formerly known as Onfido (an AI- powered digital identity solution). Our technology helps businesses verify real identities using machine learning ...

proof of concept into scalable production systems Align machine learning initiatives with product, commercial, and operational goals Advise on architecture across LLMs, agentic systems, MLOps, data pipelines, and model deployment environments Support leadership teams with AI roadmap prioritisation, delivery oversight, and capability planning Improve collaboration between product, data, and engineering … 10+ years of experience across machine learning, AI, or data-driven environments Experience leading ML teams within production-scale businesses Strong understanding of LLMs, MLOps, AI platform architecture, and scalable ML systems Experience operating within high-growth SaaS, AI-native, TechBio, or data platform businesses Ability to connect technical ...

ML Ops Engineer Role Overview Were hiring an ML Ops Engineer to own the reliability, scalability, and operational integrity of our machine-learning systems in research & production. This role sits at the intersection of data ...